Driving control system and driving control method

ABSTRACT

An imaging device includes a pixel. The pixel includes: a first electrode; a second electrode facing the first electrode; a photoelectric conversion layer between the first electrode and the second electrode, the photoelectric conversion layer converting light into signal charge; and a charge accumulation region coupled to the second electrode, the charge accumulation region accumulating the signal charge. The pixel captures first data in a first exposure period and captures second data in a second exposure period different from the first exposure period, the first exposure period and the second exposure period being included in a frame period. A length of the first exposure period is different from a length of the second exposure period. The imaging device generates multiple-exposure image data including at least the first data and the second data.

CROSS-REFERENCE OF RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.16/217,076, filed on Dec. 12, 2018, which is a Continuation ofInternational Patent Application No. PCT/JP2018/000608, filed on Jan.12, 2018, which in turn claims the benefit of Japanese Application No.2017-011651, filed on Jan. 25, 2017 and Japanese Application No.2017-011652, filed on Jan. 25, 2017, the entire disclosures of whichapplications are incorporated by reference herein.

BACKGROUND Technical Field

The present disclosure relates to a driving control system and a drivingcontrol method that assist driving of a moving body, such as a vehicleor an aircraft.

Description of the Related Art

Various traveling assistance systems that assist vehicle-travelingcontrol have been proposed in recent years. In order to controlaccelerating, braking, and steering, each traveling assistance systemrequires information about, for example, a vehicle speed, a distance toan obstacle, and so on. The vehicle speed can generally be measuredbased on the rotational speed (rpm) of wheels.

Japanese Unexamined Patent Application Publication No. 2007-81806discloses an imaging system that can measure a distance to an obstacleby stereo imaging. The imaging system includes a plurality of imagingdevices including imaging elements having photoelectric conversioncharacteristics that differ depending on subject illuminance. Makingimaging timings of a plurality of imaging devices and so on to matcheach other enables a stereo image to be accurately processed at highspeed.

SUMMARY

In recent years, the traveling assistance systems have evolveddramatically.

Expectations for such systems are high, and many requests for furtherimproving the systems have been received.

Thus, there are demands for obtaining information with higher accuracy.

In one general aspect, the techniques disclosed here feature an imagingdevice includes a pixel. The pixel includes: a first electrode; a secondelectrode facing the first electrode; a photoelectric conversion layerbetween the first electrode and the second electrode, the photoelectricconversion layer converting light into signal charge; and a chargeaccumulation region coupled to the second electrode, the chargeaccumulation region accumulating the signal charge. The pixel capturesfirst data in a first exposure period and captures second data in asecond exposure period different from the first exposure period, thefirst exposure period and the second exposure period being included in aframe period. A length of the first exposure period is different from alength of the second exposure period. The imaging device genetatesmultiple-exposure image data including at least the first data and thesecond data.

Illustrative embodiments of the present disclosure provide a drivingcontrol system that can detect the motion state of a moving body, forexample, the speed or the traveling direction thereof, a control methodfor the moving body, a vehicle-traveling control system that can detectthe motion state of a vehicle, for example, the speed or the travelingdirection thereof, and a control method for traveling of the vehicle.

It should be noted that general or specific embodiments may beimplemented as a system, a method, an integrated circuit, a computerprogram, a storage medium, or any selective combination thereof.

Additional benefits and advantages of the disclosed embodiments willbecome apparent from the specification and drawings. The benefits and/oradvantages may be individually obtained by the various embodiments andfeatures of the specification and drawings, which need not all beprovided in order to obtain one or more of such benefits and/oradvantages.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a block configuration example ofa vehicle-traveling control system including a detecting device;

FIG. 2 is a block diagram illustrating another block configurationexample of the detecting device;

FIG. 3 is a schematic diagram illustrating a configuration example ofthe imaging device;

FIG. 4A is a circuit diagram illustrating a configuration example of aunit pixel;

FIG. 4B is a circuit diagram illustrating another configuration exampleof the unit pixel;

FIG. 5 is a sectional view of the unit pixel, taken along a normaldirection of a semiconductor substrate;

FIG. 6A is a timing diagram illustrating a typical operation timing ofmultiple exposures in a unit frame period;

FIG. 6B is a schematic diagram illustrating one example ofmultiple-exposure image data;

FIG. 7A is a timing diagram illustrating an example of an applicativeoperation timing of multiple exposures in a unit frame period;

FIG. 7B is a schematic diagram illustrating one example ofmultiple-exposure image data according to an application example;

FIG. 7C is a timing diagram illustrating another example of theapplicative operation timing of the multiple exposures in the unit frameperiod;

FIG. 7D is a schematic diagram illustrating another example of themultiple-exposure image data according to the application example;

FIG. 8A is a timing diagram illustrating an example of an applicativeoperation timing of multiple exposures in a unit frame period;

FIG. 8B is a schematic diagram illustrating one example of themultiple-exposure image data according to the application example;

FIG. 8C is a timing diagram illustrating another example of theapplicative operation timing of the multiple exposure in the unit frameperiod;

FIG. 8D is a schematic diagram illustrating another example of themultiple-exposure image data according to the application example;

FIG. 9A is a sequence diagram illustrating a typical example of animaging sequence;

FIG. 9B is a sequence diagram illustrating a typical example of theimaging sequence;

FIG. 9C is a sequence diagram illustrating a typical example of theimaging sequence;

FIG. 9D is a sequence diagram illustrating a typical example of theimaging sequence;

FIG. 10 is a flowchart illustrating one example of a processing flow fordetecting a traveling direction;

FIG. 11A is a schematic diagram illustrating a state in which a hostvehicle on which the detecting device is mounted is traveling whilefollowing a vehicle ahead;

FIG. 11B is a schematic diagram illustrating a measurement image in amultiple-exposure image data that is acquired;

FIG. 11C is a schematic diagram illustrating a measurement image in amultiple-exposure image data that is acquired;

FIG. 12A is a schematic diagram illustrating a state in which the hostvehicle on which the detecting device is mounted is traveling whilefollowing the vehicle W ahead;

FIG. 12B is a schematic diagram illustrating a measurement image in amultiple-exposure image data that is acquired;

FIG. 12C is a schematic diagram illustrating a measurement image in amultiple-exposure image data that is acquired;

FIG. 13A is a schematic diagram illustrating a state in which the hostvehicle on which the detecting device is mounted is traveling whileimaging a road sign;

FIG. 13B is a schematic diagram illustrating a measurement image in amultiple-exposure image data that is acquired;

FIG. 13C is a schematic diagram illustrating a measurement image in amultiple-exposure image data that is acquired;

FIG. 14 is a flowcharted illustrating an example of a processing flowfor detecting a traveling direction and a relative speed of a vehicleand controlling braking and accelerating of the vehicle based on thedetection results;

FIG. 15 is a flowchart illustrating one example of a processing flow fordetecting a traveling direction, relative speed, and an acceleration ofthe vehicle and controlling braking and accelerating of the vehiclebased on the detection results;

FIG. 16A is a functional block diagram illustrating functional blocks ofa controller in a reference example;

FIG. 16B is a schematic diagram illustrating an image in a frame t−1;

FIG. 16C is a schematic diagram illustrating an image in a frame t;

FIG. 16D is a diagram schematically illustrating the direction ofmovement of a specific target object;

FIG. 16E is a flowchart illustrating a processing flow for an algorithmin the reference example for detecting a speed;

FIG. 17 is a functional block diagram illustrating functional blocks ofa controller for detecting a speed and an acceleration by usingmultiple-exposure image data;

FIG. 18 is a flowchart illustrating a processing flow for an algorithmfor detecting a speed and an acceleration, the algorithm being,implemented in the controller;

FIG. 19A is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data;

FIG. 19B is a schematic diagram illustrating one example of anmultiple-exposure image including a series of vehicle images;

FIG. 19C is a schematic diagram illustrating an amount-of-movementvector representing the total of vectors at one point on the vehicle;

FIG. 20 is a functional block diagram illustrating variations offunctional blocks of the controller for detecting a speed and anacceleration by using the multiple-exposure image data;

FIG. 21A is a schematic diagram illustrating a state in which a drone onwhich the detecting device is mounted is flying;

FIG. 21B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 21C is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 22A is a schematic diagram illustrating a state in which a hostvehicle on which a detecting device is mounted is traveling whileimaging a road sign;

FIG. 22B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 22C is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 22D is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 23A is a schematic diagram illustrating a state in which the hostvehicle on which the detecting device is mounted is traveling whileimaging a white line on a road;

FIG. 23B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 24A is a schematic diagram illustrating a state in which the hostvehicle on which the detecting device is mounted is traveling whileimaging a dedicated marker for measurement, the dedicated marker beingattached to a utility pole;

FIG. 24B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data that is acquired;

FIG. 25 is a flowchart illustrating one example of a processing flow fordetecting an absolute speed based on multiple-exposure image data andcontrolling the braking and accelerating of the vehicle based on theabsolute speed;

FIG. 26A is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired by a vehicle thatis traveling at a side closer to the road sign in FIG. 24A;

FIG. 26B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired by a vehicle thatis traveling at a side farther from the road sign in FIG. 24A;

FIG. 27 is a flowchart illustrating one example of a processing flow fordetecting an absolute speed and an acceleration based onmultiple-exposure image data and controlling the braking andaccelerating of the vehicle based on the absolute speed and theacceleration;

FIG. 28 is a flowchart illustrating one example of a processing flow forcontrolling the braking and accelerating of a vehicle by further usingthe vehicle speed measured by an ECU;

FIG. 29 is a flowchart illustrating one example of a processing flow fordetecting a speed based on multiple-exposure image data, furtherdetecting the traveling direction, and controlling the braking andaccelerating;

FIG. 30A is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired via generalmultiple exposures;

FIG. 30B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired via the generalmultiple exposures;

FIG. 30C is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired via the generalmultiple exposures, when the distance between a vehicle traveling a headand the host vehicle is small;

FIG. 30D is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired via the generalmultiple exposures, when the distance between the vehicle travelingahead and the host vehicle is large;

FIG. 31 is a flowchart illustrating one example of a processing flow fordetecting a relative speed and an acceleration based onmultiple-exposure image data, further detecting a traveling direction,and controlling braking/accelerating;

FIG. 32 is a flowchart illustrating one example of a processing flow forcontrolling braking/accelerating by using a vehicle speed measured bythe ECU;

FIG. 33A is a schematic diagram illustrating a state in which thevehicle enters a curved road;

FIG. 33B is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired by imaging theoutside of the curved road when the vehicle enters the curved road; and

FIG. 33C is a schematic diagram illustrating one example of an imagerepresented by multiple-exposure image data acquired by imaging theinside of the curved road.

DETAILED DESCRIPTION

First, a description will be given of problems with the related artwhich were considered by the present inventor. In recent years, thetraveling assistance systems have evolved dramatically. The systems areturning from systems in which automobile driving operation by the humanis assisted into automobile-centric systems in which an automobileitself obtains information, makes decisions, and performs drivingoperation. Expectations for such systems are high, and many requests forfurther improving the systems have been received. It cannot necessarilybe said that, in the related technology, information required forvehicle-traveling control has been obtained with high accuracy. Thus,there are demands for obtaining the information with higher accuracy.

Heretofore, the speed of a vehicle has been generally measured based ona pulse signal that is proportional to the rotational speed of wheels.However, owing to wear of the tires on the wheels and a measurementenvironment, its measurement error and uncertainty are not constant. Forexample, there are possibilities that the tires skid during right turnor left turn on a frozen road or the wheels are locked during braking.In such a state, it is difficult to accurately measure the vehicle speedbased on the pulse signal. In the future, in advanced driver-assistancesystems (ADAS), autonomous cars, and so on whose further advancementsare desired, it is necessary that information needed for travelingcontrol be properly acquired, and the control be performedinstantaneously.

In view of such issues, the present inventor has conceived a noveldetecting device. One non-limiting and exemplary embodiment provides amoving-body control system that can detect the motion state of a movingbody, for example, the speed or the traveling direction thereof, and ismainly aimed to provide a driving control system that can detect themotion state of a vehicle, for example, the speed or the travelingdirection thereof. An overview of one aspect of the present disclosureis described in the following items.

[Item 1] A driving control system includes:

an imaging device that is installed on a moving body and that images atarget object in a first frame period a plurality of times to generate amultiple-exposure image data including a first image data and a secondimage data; and

a processor that detects a relative motion state of the moving body withrespect to the target object, based on the first image data and thesecond image data included in the multiple-exposure image data, wherein

the imaging device images the target object with a first sensitivity ina first exposure period in the first frame period to generate the firstimage data and images the target object with a second sensitivity in asecond exposure period in the first frame period to generate the secondimage data, the second exposure period being different from the firstexposure period, and the second sensitivity being different from thefirst sensitivity.

[Item 2] The driving control system according to item 1 may furtherinclude:

a first control device, wherein

the first control device generates a signal for causing the motion stateof the moving body to change, based on the relative motion state of themoving body.

[Item 3] The driving control system according to item 2 may furtherinclude:

a second control device, wherein

the second control device may cause the motion state of the moving bodyto change, based on the signal.

[Item 4] The driving control system according to item 1 may furtherinclude:

a first control device, wherein

the target object may be fixed to another moving body, and

the first control device may generate a signal for causing a motionstate of the other moving body to change, based on the relative motionstate of the moving body.

[Item 5] The driving control system according to item 4 may furtherinclude:

a second control device, wherein

the second control device may cause the motion state of the other movingbody, based on the signal.

[Item 6] In the driving control system according to item 1, the movingbody may be a vehicle.

[Item 7] In the driving control system according to item 1, the targetobject may be stationary relative to a ground surface, and

the processor may detect an absolute speed of the moving body.

[Item 8] In the driving control system according to item 1, the targetobject may be stationary relative to a ground surface; and

the processor may detect a distance between the moving body and thetarget object, based on the first image data, and may generate positioninformation of the moving body, based on position information of thetarget object and the distance.

[Item 9] In the driving control system according to item 1, the firstimage data may be generated by a first imaging in the first frameperiod; and

the second image data may be generated by a last imaging in the firstframe period.

[Item 10] In the driving control system according to item 1, of aplurality of image data included in the multiple-exposure image data, atleast one image data other than the second image data may be generatedby imaging the target object with the first sensitivity.

[Item 11] In the driving control system according to item 1, of aplurality of image data included in the multiple-exposure image data, atleast one image data other than the first image data may be generated byimaging the target object with the second sensitivity.

[Item 12] In the driving control system according to item 1, theprocessor may detect a traveling direction of the moving body withrespect to the target object, based on the first image data and thesecond image data.

[Item 13] In the driving control system according to item 1, theprocessor may detect a relative speed of the moving body with respect tothe target object, based on the first image data and the second imagedata.

[Item 14] In the driving control system according to item 1, theprocessor may detect an acceleration of the moving body with respect tothe target object, based on the first image data and the second imagedata.

[Item 15] In the driving control system according to item 1, theprocessor may switch, every predetermined period, between a first modein which a traveling direction of the moving body with respect to thetarget object is detected and a second mode in which a relative speed ofthe moving body with respect to the target object is detected, based onthe first image data and the second image data.

[Item 16] The driving control system according to item 1 may furtherinclude:

a control device, wherein

the target object may be fixed to another moving body;

the processor may detect a change in a distance between the moving bodyand the target object, based on the first image data and the secondimage data; and

when it is detecting that the distance has become smaller than apredetermined value, the control device may generate a signal forcausing a motion state of the moving body or the other moving body tochange so that the distance increases.

[Item 17] The driving control system according to item 1 may furtherinclude:

a control device, wherein

the target object may be fixed to another moving body; and

the processor

-   -   may detect a change in a distance between the moving body and        the target object, based on the first image data and the second        image data, and    -   may generate a signal for causing a motion state of the moving        body or the other moving body to change so that the distance        decreases, when it is detected that the distance has become        larger than a predetermined value.

[Item 18] In the driving control system according to item 1, theprocessor may detect a relative motion state of the moving body withrespect to the target object, based on feature points of images of thetarget object in the first image data and the second image data.

[Item 19] In the driving control system according to item 3, the firstcontrol device and the second control device may be a common controldevice.

[Item 20] A driving control method includes:

imaging a target object with a first sensitivity in a first exposureperiod in a first frame period to generate a first image data, andimaging the target object with a second sensitivity in a second exposureperiod in the first frame period to generate a second image data, byusing an imaging device installed on a moving body, to thereby generatea multiple-exposure image data including the first image data and thesecond image data, the second exposure period being different from thefirst exposure period, and the second sensitivity being different fromthe first sensitivity;

detecting a relative motion state of the moving body with respect to thetarget object, based on the first image data and the second image dataincluded in the multiple-exposure image data;

generating a signal for causing a motion state of the moving body tochange, based on the relative motion state of the moving body; and

causing the motion state of the moving body to change, based on thesignal.

[Item 21] A driving control method includes:

imaging a target object fixed to another moving body with a firstsensitivity in a first exposure period in a first frame period togenerate a first image data, and imaging the target object with a secondsensitivity in a second exposure period in the first frame period togenerate a second image data, by using an imaging device installed on amoving body, to thereby generate a multiple-exposure image dataincluding the first image data and the second image data, the secondexposure period being different from the first exposure period, thesecond sensitivity being different from the first sensitivity;

detecting a relative motion state of the moving body with respect to thetarget object, based on the first image data and the second image dataincluded in the multiple-exposure image data;

generating a signal for causing a motion state of the other moving bodyto change, based on the relative motion state of the moving body; and

causing the motion state of the other moving body to change, based onthe signal.

According to one aspect of the present disclosure, a multiple-exposureimage data acquired by performing a plurality of image captures in oneframe period is used, in order to recognize the motion state or thesurrounding state of a moving body, for example, a vehicle or anaircraft. Thus, for example, it is possible to significantly reduce theamount of computation performed in order to determine the speed and thetraveling direction of a vehicle, compared with a case in which onepiece of image data is acquired for each frame period and the acquiredplurality of pieces of image data is used to detect the motion state.

When the motion state of a target object is detected using a pluralityof pieces of image data, the detection interval is limited by thereading speed of an image sensor. In contrast, the multiple-exposureimage data includes a plurality of pieces of image data that aresuperimposed. Thus, in the present disclosure, the detection interval ofa target object is defined by an exposure interval of multipleexposures. Hence, according to the present disclosure, the measurementspeed can be significantly enhanced, and the measurement accuracy can beimproved. Also, according to the present disclosure, since the detectioninterval is small, the amount of movement of a target object in thedetection interval is small, thus making it possible to more finelydetect the motion state of the target object. Hence, when the motionstate of a target object is predicted from a result of the detection, animprovement in the prediction probability can be expected, and inaddition, since the motion state is detected using one piece ofmultiple-exposure image data, a computational area needed for detectionin an image can be narrowed down, and the amount of computation can bereduced.

Embodiments of the present disclosure will be described below in detailwith reference to the accompanying drawings. The embodiments describedbelow each represent a general or specific example. Numerical values,shapes, materials, constituent elements, the arrangement and theconnection forms of constituent elements, steps, the order of steps, andso on described in the embodiments below are examples and are notintended to limit the present disclosure. Various aspects describedherein can be combined together, as long as such a combination does notcause contradiction. Also, of the constituent elements in theembodiments below, constituent elements not set forth in the independentclaims that represent the broadest concept will be described as optionalconstituent elements. In the following description, constituent elementshaving substantially the same functions are denoted by the samereference numerals, and descriptions thereof may be omitted.

The present disclosure relates to a technology for mainly detecting therelative traveling direction of a moving body and the speed or theacceleration of the moving body. The relative traveling direction of amoving body means, for example, the relative traveling direction of amoving body with respect to another moving body or the travelingdirection of a moving body with respect to a stationary body. Also, therelative speed and acceleration of a moving body mean the relative speedand acceleration of a moving body with respect to another moving body.

The present disclosure further relates to a technology for mainlydetecting the absolute traveling direction of a moving body and thespeed and acceleration of the moving body. The absolute travelingdirection of a moving body means, for example, the absolute travelingdirection of a moving body itself. Also, the absolute speed andacceleration of a moving body mean the absolute speed and accelerationof a moving body itself.

Herein, the states of motions of a moving body which include theabove-described traveling direction, speed, and acceleration may becollectively referred to as a “motion state” of a moving body.

Herein, the moving body refers to any object that moves. Examples of themoving body include a human, a vehicle, industrial control equipment, aself-contained robot, and an aircraft. Examples of the vehicle includean automobile, a motorcycle, and a train. Examples of the aircraftinclude an airship and a multicopter. The multicopter is, for example, adrone, regardless of whether it is manned or unmanned.

First Embodiment <1.1. Configurations of Vehicle-Traveling ControlSystem 1000 and Detecting Device 1>

FIG. 1 illustrates a block configuration example of a vehicle-travelingcontrol system 1000 including a detecting device 1.

The detecting device 1 in the present embodiment is a device mounted ona vehicle and mainly detects a relative traveling direction of avehicle. The vehicle is, for example, an automobile. The detectingdevice 1 can be arranged at, for example, at least one of a front sideand a rear side of the vehicle. This makes it possible to image targetobjects in a wide range at either the front side or the rear side of thevehicle.

The detecting device 1 can communicably connect to, for example, adistance measuring unit 600, a traveling-direction measuring unit 700,and an electronic control unit 800 through a bus. The electronic controlunit is hereafter referred to as “ECU”. Communication between theconstituent elements is performed in a wired or wireless manner. Forexample, communication using a controller area network (CAN), which isan in-vehicle network, is possible. This constructs thevehicle-traveling control system 1000 in which the ECU 800 serves as acore. The vehicle-traveling control system 1000 is desirably mounted,for example, on an automobile. In addition, the vehicle-travelingcontrol system 1000 can be constructed by a plurality of vehiclesincluding a host vehicle and a surrounding vehicle that travels in thesurroundings of the host vehicle. In the vehicle-traveling controlsystem 1000, the distance measuring unit 600 and the traveling-directionmeasuring unit 700 are not essential, as described below.

The detecting device 1 includes an imaging device 100, an optical system200, an image signal processor 300, an image transmission interface 400,and a control device 500. Hereinafter, the control device is referred toas a “controller”, and the image signal processor is referred to as an“ISP”.

The imaging device 100 is, for example, a complementary metal-oxidesemiconductor (CMOS) image sensor. The imaging device 100 can acquiremultiple-exposure image data of a subject. Details of the imaging device100 are described later. The imaging device 100 is typically mounted onthe host vehicle.

The optical system 200 has a known lens group constituted by a focuslens, a zoom lens, and so on. In the lens group, for example, the focuslens moves in an optical axis direction. This makes it possible toadjust a subject-image focusing position in the imaging device 100.

The ISP 300 is a processor for performing image processing on image dataoutput from the imaging device 100. The ISP 300 first receives outputdata from the imaging device 100. The output data from the imagingdevice 100 is, for example, uncompressed, unprocessed raw data. The ISP300 can perform, for example, gamma correction, color interpolationprocessing, space interpolation processing, and automatic whitebalancing processing on the output data from the imaging device 100.

The image transmission interface 400 is an interface (IF) for outputtingmultiple-exposure image data and so on to outside thereof. The outsideof the image transmission interface 400 is, for example, the ECU 800.For example, the image transmission interface 400 can communicate withthe ECU 800 through a CAN. The multiple-exposure image data and so onmay be directly output as raw data or may be output according to aspecified format after being subjected to image compression orpredetermined image processing.

The controller 500 is a control circuit for controlling the entiredetecting device 1 and functions as a computational processing device.The controller 500 can process the multiple-exposure image data from theISP 300. The controller 500 can detect, for example, a relativetraveling direction and a relative speed of the vehicle, based on themultiple-exposure image data. The controller 500 can be mounted on thehost vehicle or a surrounding vehicle that travels in the surroundingsof the host vehicle.

The controller 500 includes, for example, an output interface 510 havinga voltage control circuit 511, an input interface 520, a program memory530, a working memory 540, and a microcontroller 550.

The input interface 520 is an interface for receiving themultiple-exposure image data output from the ISP 300.

The microcontroller 550 temporarily loads a program, pre-stored in theprogram memory 530, to the working memory 540 and performs variousoperations in accordance with a command group of the program. Theprogram memory 530 is, for example, a read-only memory (ROM), and theworking memory 540 is, for example, a random-access memory (RAM). Theprogram stored in the program memory 530 has, for example, a commandgroup for controlling the imaging device 100.

The output interface 510 is an interface for outputting control signalsto the imaging device 100. The output interface 510 includes the voltagecontrol circuit 511. For example, the voltage control circuit 511generates a desired voltage to be applied to a photoelectric conversionlayer in pixels in the imaging device 100. The voltage control circuit511 supplies the voltage to a transparent electrode 109A, which isdescribed later with reference to FIG. 5. The voltage control circuit511 can control, for example, a global shutter in the imaging device100. The present disclosure can employ, in addition to the voltagecontrol circuit 511, any other configuration that can realize the globalshutter in the imaging device 100.

Since the configuration and so on of the controller 500 are not inherentportions in the present disclosure, detailed descriptions thereof areomitted.

FIG. 2 illustrates another block configuration example of the detectingdevice 1.

In the configuration example in FIG. 1, the ISP 300 is in a chipdifferent from that of the imaging device 100 and is provided externalto the imaging device 100. On the other hand, in the configurationexample in FIG. 2, the imaging device 100 and the ISP 300 areimplemented in the same chip. According to this configuration example,it is possible to process image data at higher speed and it is possibleto reduce the cost of the hardware. Although the detecting device 1 hasbeen described as including the imaging device 100 or 100′, thedetecting device 1 does not necessarily have to include the imagingdevice 100 or 100′, and the imaging device 100 or 100′ may be providedoutside the detecting device 1.

FIG. 3 illustrates a configuration example of the imaging device 100.

The imaging device 100 includes a pixel array constituted by a pluralityof unit pixels 101 arranged two-dimensionally. Although, in practice,millions of unit pixels 101 can be arranged two-dimensionally, FIG. 3illustrates a state thereof while paying attention to the unit pixels101 arranged in a 2×2 matrix.

The imaging device 100 includes the plurality of unit pixels 101, a rowscanning circuit 102, a column scanning circuit 103, current sources 104provided for respective columns, and analog-to-digital (AD) conversioncircuits 105. Horizontal signal lines 107 are provided for respectiverows, and vertical signal lines 108 are provided for respective columns.Each unit pixel 101 is electrically connected to the row scanningcircuit 102 through the corresponding horizontal signal line 107 and iselectrically connected to the column scanning circuit 103 through thecorresponding vertical signal line 108.

For example, a common power-supply line 106 is connected to all of theunit pixels 101. A common voltage is supplied to all of the unit pixels101 through the common power-supply line 106. Pixel signals based onoptical signals photoelectrically converted in the unit pixels 101 areanalog signals, which are converted into digital signals by the ADconversion circuits 105. The signals converted into the digital signalsare output from the column scanning circuit 103 as output signals. Inthis configuration, when the start timings and the end timings ofexposures in a plurality of unit pixels 101 are the same, a globalshutter function is realized. However, in the present disclosure, it issufficient that the start timings and the end timings of exposures in atleast two unit pixels 101 of the of unit pixels 101 are the same. The ADconversion circuits 105 do not have to be provided for the respectivecolumns, and the pixel signals may be directly output as analog signals.The pixel signals from the plurality of unit pixels 101 can be subjectedto addition or subtraction, and values after the computation can beoutput from the column scanning circuit 103. Alternatively, the pixelsignals from the plurality of unit pixels 101 can be directly outputfrom the column scanning circuit 103.

FIG. 4A illustrates a configuration example of each unit pixel 101. FIG.5 schematically illustrates a section of the unit pixel 101, taken alonga normal direction of a semiconductor substrate 109D.

The unit pixel 101 illustrated in FIG. 4A includes a photoelectricconverter 109, a floating diffusion, an amplifying transistor M1, aselecting transistor M2, and a reset transistor M3. The floatingdiffusion is hereinafter referred to as an “FD”. The photoelectricconverter 109 photoelectrically converts incident light. The FDaccumulates electrical charge. The amplifying transistor M1 amplifiesthe electrical charge accumulated in the FD. The selecting transistor M2selects whether or not an amplified signal is to be output to thevertical signal line 108. The reset transistor M3 resets the FD to adesired reset potential Vrst. Herein, a circuit constituted by theamplifying transistor M1, the selecting transistor M2, the resettransistor M3, and so on is referred to as a “signal processingcircuit”. The signal processing circuit is electrically connected to thephotoelectric converter 109 to detect an electrical signal.

The photoelectric converter 109 in the unit pixel 101 has thetransparent electrode 109A, a pixel electrode 1098, and a photoelectricconversion layer 109C arranged between the transparent electrode 109Aand the pixel electrode 1098. The pixel electrode 1098 is electricallyconnected to the signal processing circuit. The FD is provided in thesemiconductor substrate 109D and is electrically connected to the pixelelectrode 1098 via a contact plug 109E. Light is incident on thephotoelectric conversion layer 109C from the transparent electrode 109Aside of the photoelectric conversion layer 109C. When a bias voltage isapplied between the transparent electrode 109A and the pixel electrode109B, an electrical field is generated. One of positive and negativeelectrical charge generated by the photoelectric conversion is collectedby the pixel electrode 1098 and is accumulated in the FD.

A potential difference between the transparent electrode 109A and thepixel electrode 1098 is controlled through the above-describedpower-supply line 106. For example, a change from a state in which thepotential difference between the transparent electrode 109A and thepixel electrode 1098 is large to a state in which the potentialdifference is small makes it possible to reduce the amount of electricalcharge photoelectrically converted in the photoelectric conversion layer109C. Alternatively, adjusting the potential difference also makes itpossible to reduce the amount of electrical charge photoelectricallyconverted in the photoelectric conversion layer 109C to zero.

In the case of this configuration, merely controlling the magnitude ofthe bias voltage applied to the photoelectric conversion layer 109Cmakes it possible to control generation and accumulation of theelectrical charge in the unit pixel 101. That is, an electrical-chargetransfer transistor and an element, such as a capacitor, foraccumulating transferred electrical charge do not have to be added toeach unit pixel as in the related art. Controlling the bias voltage isperformed by, for example, the voltage control circuit 511 in thecontroller 500. Simultaneously controlling the bias voltages for two ormore of the plurality of unit pixels 101 allows a shutter to besimultaneously released between the two or more unit pixels. That is, aglobal shutter is realized among those unit pixels. A global shutter maybe realized among all of the unit pixels 101. Alternatively, a globalshutter may be realized among the unit pixels 101 that exist in aspecific imaging area or may be realized among specific unit pixels 101.In addition, the shutter may be released in a plurality of separatestages.

When a voltage between the transparent electrode 109A and the pixelelectrode 1098 is reduced in a state in which signal charge is alreadyaccumulated in the FD, the accumulation of electrical charge in the FDstops. Thereafter, when the voltage between the transparent electrode109A and the pixel electrode 1098 is increased, signal charge can befurther accumulated in the FD. Thus, controlling the bias voltage at aplurality of different timings in one frame period makes it possible toacquire a plurality of pieces of image data in one frame period. Thatis, multiple-exposure image data in which a plurality of pieces of imagedata is multiplexed can be acquired in one frame period.

With known imaging elements, a plurality of pieces of image data needsto be treated as a group of pieces of data acquired in respectivedifferent frame periods. According to the present disclosure, themultiple-exposure image data can be handled as one piece of data. Thus,the present disclosure has advantages in that the amount of data can bereduced and load on data processing in a circuit at a subsequent stagecan be reduced.

In addition, when the imaging device 100 generates multiple-exposureimage data, bias voltages that are different from each other may beapplied between electrodes at the respective timings in one frameperiod. This makes it possible to acquire multiple-exposure image dataincluding a plurality of pieces of image data having sensitivities thatare different from each other. Herein, such multiple exposures may bereferred to as “multiple exposures via sensitivity modulation”.

With known imaging elements, it is impossible to modulate thesensitivity by controlling a voltage applied to unit pixels. The presentdisclosure has an advantage in that the sensitivity can be modulated bycontrolling the magnitude of the bias voltage. Since the above detaileddescription of the multiple exposures via sensitivity modulation isgiven in, for example, Japanese Unexamined Patent ApplicationPublication No. 2007-104113 by the present applicant, the descriptionthereof is omitted herein. These entire contents of the disclosure areincorporated herein for reference.

FIG. 4B illustrates another configuration example of the unit pixel 101.

The unit pixel 101 in FIG. 4B includes a photodiode (hereinafterreferred to as a “PD”) as the photoelectric converter. Typically, theunit pixel 101 in this configuration example further includes anelectrical-charge transfer transistor M4 for transferring electricalcharge generated in the PD to the FD. In this manner, an image sensorconstituted by unit pixels having PDs may also be utilized as theimaging device 100. Although FIG. 4B illustrates a configuration inwhich the electrical-charge transfer transistor M4 is provided, aconfiguration in which the electrical-charge transfer transistor M4 isnot provided may be used.

Reference is made to FIGS. 1 and 2 again.

Data processed by the ISP 300 or an imaging device 100′ is read asmultiple-exposure image data, which is output to the image transmissioninterface 400 and the controller 500. In addition to themultiple-exposure image data, naturally, the imaging device 100 maygenerate image data via a single exposure.

The distance measuring unit 600 can measure a distance between the hostvehicle and a target object. The distance measuring unit 600 can berealized by, for example, a device, such as a time-of-flight (TOF)sensor, a laser radar, and a sonar.

The traveling-direction measuring unit 700 can measure a relativetraveling direction of the host vehicle relative to a target object. Therelative traveling direction of the host vehicle relative to a targetobject refers to, for example, the positional relationship of the hostvehicle relative to a target object and the direction of change thereof.The traveling-direction measuring unit 700 can be realized by, forexample, devices, such as a TOF, a laser radar, and a sonar. The targetobject may be a moving body or may be a stationary body.

As described above, the distance measuring unit 600 and thetraveling-direction measuring unit 700 are not essential. As describedbelow, analyzing the multiple-exposure image data makes it possible toobtain information, such as the distance and the relative travelingdirection. Acquiring those pieces of information through data analysismakes it possible to reduce the number of pieces of hardware in thevehicle-traveling control system 1000. As a result, thevehicle-traveling control system 1000 can be simplified and optimized.Naturally, the distance detection by the device and by data analysis mayalso be selectively used depending on the type of control.

The ECU 800 is a unit that serves as a core of an in-vehicle network andthat performs engine control as well as various types of vehicle controlon braking, steering, accelerating, and so on. For example, the ECU 800can control braking and accelerating of the vehicle, based on an outputfrom the detecting device 1. Also, the ECU 800 can perform variouscomputations of the detecting device 1.

<1.2. Basic Operation of Imaging Device 100>

First, a basic operation of the imaging device 100 will be describedwith reference to FIGS. 6A and 6B.

FIG. 6A illustrates a typical operation timing of multiple exposures ina unit frame period. FIG. 6B illustrates one example of an imagerepresented by multiple-exposure image data. In FIG. 6A, VD represents astart pulse in the unit frame period. A period between two start pulsescorresponds to the unit frame period. A control signal V2 represents abias voltage applied to the photoelectric conversion layer 109C in theunit pixel 101.

A plurality of pieces of image data acquired via multiple exposures inone frame period is acquired according to the level of the controlsignal V2 generated by the voltage control circuit 511. Each period inwhich the control signal V2 is high is an exposure period, and eachperiod in which the control signal V2 is low is a non-exposure period.In each exposure period, the electrical charge generated byphotoelectric conversion in the photoelectric conversion layer 109Cmoves to the pixel electrodes 109B. On the other hand, in eachnon-exposure period, the electrical charge generated by thephotoelectric conversion in the photoelectric conversion layer 109Crecouples and vanishes.

The imaging device 100 in the present embodiment can change the exposureperiod, the number of exposures, and the sensitivity. Specifically, thevoltage control circuit 511 can control exposures by changing the pulsewidth and the pulse amplitude of the control signal V2 in a unit frameperiod.

FIG. 6A illustrates an example in which four or more exposures areexecuted in a unit frame period without changing the sensitivity.However, it is acceptable that the number of exposures in the unit frameperiod is two or more. The imaging device 100 generatesmultiple-exposure image data including a plurality of pieces of imagedata (first, second, . . . , and n-th image data; n is an integergreater than or equal to 2) acquired in the respective exposures.Accordingly, the multiple-exposure image data includes at least thefirst and second image data. The first image data is acquired in a firstexposure period, and the second image data is acquired in a secondexposure period. Herein, multiple exposures that are performed withoutchanging the sensitivity of pixels in respective exposure periods may bereferred to as “general multiple exposures”. According to the generalmultiple exposures, for example, when a stationary body is imaged,images of the subject are captured by, for example, a plurality of sameunit pixels 101 in the pixel array, illustrated in FIG. 3, in theindividual exposure periods. In contrast, when a moving body is imaged,images of the subject are captured by a plurality of different unitpixels 101 in the individual exposure periods. In this case, theexpression “images are captured by a plurality of different unit pixels101 in the individual exposure periods” refers to, for example, aplurality of unit pixels 101 by which a subject is imaged in the firstexposure period and a plurality of unit pixels 101 by which the subjectis imaged in the second exposure period do not match partly orcompletely. As a result, for example, image data acquired via four ormore exposures are included in one piece of multiple-exposure image dataas four or more images that are independent or that partly overlap eachother. FIG. 6B illustrates one example of an image represented bymultiple-exposure image data acquired by imaging, four times at timingsdifferent from each other, the license plate of a vehicle that istraveling ahead of the host vehicle in a unit frame period.

Next, an applicative operation of the imaging device 100 will bedescribed with reference to FIGS. 7A to 7D.

FIG. 7A illustrates an example of an applicative operation timing ofmultiple exposures in a unit frame period. FIG. 7B illustrates oneexample of an image represented by multiple-exposure image dataaccording to an application example. FIG. 7C illustrates another exampleof the applicative operation timing of the multiple exposures in theunit frame period. FIG. 7D illustrates another example of the imagerepresented by the multiple-exposure image data according to theapplication example.

In this application example, multiple exposures via sensitivitymodulation are executed by changing the level of the control signal V2between exposures. Thus, the sensitivity and the amount of exposurediffer between two exposure periods. The level of the control signal V2is changed, for example, by changing the amplitude of the pulse. FIG. 7Aillustrates an example in which four or more multiple exposures in whichthe sensitivities differ from each other are executed in a unit frameperiod. The control signal V2 is set to a voltage whose level differsfor each exposure. The level of the control signal V2 may increasemonotonically, as illustrated in FIG. 7A. Alternatively, the level ofthe control signal V2 may decrease monotonically, as illustrated in FIG.7C. When the change in the level of the control signal V2 is amonotonical increase, for example, as illustrated in FIG. 7A, lightnessin first image data acquired in a first exposure period is the lowest,and lightness in fourth image data acquired in a fourth exposure periodis the highest. The imaging device 100 generates multiple-exposure imagedata including a plurality of pieces of image data that were acquiredfrom individual exposures and in which the sensitivities differ fromeach other. The control signal V2 can be arbitrarily set and may takevarious patterns depending on the detection purpose. For example, thelevel of the control signal V2 does not have to increase monotonicallyor decrease monotonically or may be caused to increase or decrease in anarbitrary pattern.

FIGS. 7B and 7D each illustrate one example of an image represented bymultiple-exposure image data acquired by imaging, four times in a unitframe period, the license plate of a vehicle traveling ahead of the hostvehicle.

In this application example, in the multiple-exposure image data,lightness differs among four images acquired by imaging a subject havingmotion. Thus, the motion of the subject can be checked in a time series.Herein, the lightness is one example of a “degree of a common displayattribute”. The degree of a common display attribute can be, forexample, a degree of color saturation and hue, other than the lightness.

FIGS. 6B, 7B, and 7D each illustrate one example of an image representedby multiple-exposure image data acquired by imaging the same subjecthaving motion. When all of the degrees of a common display attribute inthe exposures are the same, the image data illustrated in FIG. 6B isacquired. When the degrees of a common display attribute differ amongthe exposures, the image data illustrated in FIG. 7B or 7D is acquired.FIG. 7B shows that the higher the lightness of an image is, the lateracquired subject image in a time series the image is. Also, FIG. 7Dshows that the lower the lightness of an image is, the later acquiredsubject image in a time series the image is. This means that therelative traveling direction and the relative speed of the host vehiclewith respect to a vehicle traveling ahead can be detected based on themultiple-exposure image data, as described below. The host vehicle isone example of a first moving body, and the vehicle traveling ahead isone example of a second moving body.

For example, in FIG. 7B, the higher the lightness of the image of thelicense plate is, the smaller the displayed image is. That is, the laterthe image is acquired in a time series, the smaller the size of theimage is. Therefore, it can be detected that the host vehicle isrelatively moving backward or is relatively decelerating relative to thevehicle traveling ahead. Similarly, for example, in FIG. 7D, the lowerthe lightness of the image of the license plate is, the smaller the sizeof the displaced image is. That is, the later the image is acquired in atime series, the smaller the size of the image is. Therefore, it can bedetected that the host vehicle is relatively moving backward or isrelatively decelerating relative to the vehicle traveling ahead.

Also, as another example, it is possible to modulate the sensitivity byvarying the exposure period from one exposure to another. One example ofthe modulation will be described below.

FIG. 8A illustrates an example of an applicative operation timing ofmultiple exposures in a unit frame period. FIG. 8B illustrates oneexample of an image represented by multiple-exposure image dataaccording to an application example. FIG. 8C illustrates another exampleof the applicative operation timing of the multiple exposures in theunit frame period. FIG. 8D illustrates another example of the imagerepresented by the multiple-exposure image data according to theapplication example.

In this application example, the lengths of the exposures from a firstexposure period to a fourth exposure period differ from each other.Although the lengths of the exposures in all the exposure periods differin this application example, the lengths of at least two exposureperiods may differ. The exposure period, that is, the pulse width of thecontrol signal V2, is varied between the exposures to thereby modulatethe sensitivity. FIG. 8B shows that the higher the lightness of an imageis, the later acquired image in a time series the image is. Also, FIG.8D shows that the lower the lightness of an image is, the later acquiredimage in a time series the image is.

For example, in FIG. 8B, the higher the lightness of the image of thelicense plate is, the smaller the displayed image is. That is, the laterthe image is acquired in a time series, the smaller the size of theimage is. Therefore, it can be detected that the host vehicle isrelatively moving backward or is relatively decelerating relative to thevehicle traveling ahead. Similarly, for example, in FIG. 8D, the lowerthe lightness of the image of the license plate is, the smaller the sizeof the displaced image is. That is, the later the image is acquired in atime series, the smaller the size of the image is. Therefore, it can bedetected that the host vehicle is relatively moving backward or isrelatively decelerating relative to the vehicle traveling ahead.

Next, some typical examples of an imaging sequence will be describedwith reference to FIGS. 9A to 9D.

FIGS. 9A to 9D illustrate typical examples of an imaging sequence.

As illustrated in FIGS. 9A and 9B, in one imaging sequence, sensitivitymodulation may be applied to only a frame period for sensing a travelingdirection, and the traveling direction may be detected based onmultiple-exposure image data acquired in the frame period. In addition,the general multiple-exposure image capture may be performed in aremaining frame period. A frame for sensing a traveling direction willhereinafter be referred to as a “frame for direction detection”.

As illustrated in FIG. 9C, through constant application of sensitivitymodulation in each frame period of one imaging sequence, the travelingdirection may be constantly detected based on multiple-exposure imagedata acquired in each frame period. Also, as illustrated in FIG. 9D, aperiod of the frame for direction detection may be periodically set in aplurality of frame periods in one imaging sequence, and throughapplication of the sensitivity modulation to only the set frame period,the traveling direction may be detected based on multiple-exposure imagedata acquired in the period. Also, in accordance with control of thecontroller 500, the imaging device 100 may be caused to operate, whileswitching the configurations of some of the above-described imagingsequences according to a traveling condition.

In one imaging sequence, a period of a frame for sensing a travelingstate may be set, and through detection of a speed based onmultiple-exposure image data acquired in the period, the exposureinterval in multiple-exposure imaging in a remaining frame period may becontrolled based on the speed. A frame for sensing the traveling stateis hereinafter referred to as a “frame for traveling-state detection”.The frame for traveling-state detection may be periodically set in aplurality of frame periods in one imaging sequence. When the amount ofdata acquired is too small relative to a vehicle speed, it is difficultfor the detecting device 1 to accurately follow the speed. Also, whenthe amount of data acquired is too large, it leads to an increase in theamount of computation and an increase in the power consumed by a chip.As a result, it is difficult to perform high-speed processing.Meanwhile, setting the frame for traveling-state detection in an imagingsequence, as described above, and controlling the exposure interval ofsubsequent image captures based on its measurement result makes itpossible to appropriately put the amount of data acquired into anappropriate range and makes it possible to maintain the detectionaccuracy.

<1.3. Specific Example 1 of Operation of Detecting Device 1>

Specific example 1 of the operation of the detecting device 1 will bedescribed with reference to FIGS. 10 to 12C.

When the engine in the host vehicle starts, the imaging device 100according to the present embodiment starts imaging. The imaging device100 images a specific target object included in another vehicle. Basedon first image data and second image data of a specific target objectimaged via sensitivity modulation, the controller 500 can detect therelative traveling direction of the host vehicle with respect to theother vehicle. The specific target object is an object whose dimensionsare specified by a standard. The specific target object is, for example,the license plate of another vehicle or lamps, such as headlights orbrake lights of another vehicle.

FIG. 10 illustrates one example of a processing flow for detecting thetraveling direction. Herein, a description will be given of an examplein which the controller 500 executes individual processes to detect therelative traveling direction or the relative speed of the host vehicleor both thereof. A main body for the processes may be the ECU 800. Inother words, the ECU 800 may detect the relative traveling direction orthe relative speed of the host vehicle or both thereof, based on outputdata from the detecting device 1.

The controller 500 can detect a feature of a specific target object, forexample, by using a known object-recognition algorithm. Upon detectingthe feature, the controller 500 starts booting a program for detecting avehicle traveling direction. Then, the process proceeds to a process fordetecting a relative traveling direction (START and step S100 in FIG.10).

The controller 500 starts detection of the relative traveling direction(step S110). For example, in the imaging sequence illustrated in FIG.9A, the controller 500 sets a frame for direction detection.

Now, consider acquiring multiple-exposure image data in accordance withthe general multiple exposures described above with reference to FIG.6A. For example, in the multiple-exposure image data illustrated in FIG.6B, which of arbitrary two pieces of image data is acquired first is notdistinguishable. This is due to the degrees of a common displayattribute being the same between the two pieces of image data. In themultiple-exposure image data illustrated in FIG. 6B, the common displayattribute is lightness. That is, it is difficult to detect the relativetraveling direction of the host vehicle with respect to a vehicle ahead,based on the multiple-exposure image data. More specifically, a cleardistinction cannot be made as to whether the host vehicle relativelyaccelerates to reduce the distance to the vehicle ahead or the hostvehicle relatively decelerates to increase the distance to anothervehicle.

The imaging device 100 performs a plurality of image captures with thesensitivity per unit time being varied by changing the level of thecontrol signal V2 between a plurality of exposures in a unit frameperiod, for example, as illustrated in FIG. 7A or 7C. As a result, it ispossible to acquire multiple-exposure image data including a pluralityof pieces of image data in which the degrees of the common displayattribute differ from each other. The controller 500 receives themultiple-exposure image data output from the imaging device 100. Thecontroller 500 can measure a difference in the degrees of the commondisplay attribute, based on the multiple-exposure image data, and candistinguish which of two pieces of image data was acquired earlier.Thus, the controller 500 can detect the relative traveling direction,based on the lightness of license plate images in first and second imagedata (step S120).

Thereafter, the controller 500 determines whether or not the imagecapture and the traveling-direction detection are to be continued (stepS130). When the image capture and the traveling-direction detection areto be continued, the controller 500 repeats the above-described flow. Onthe other hand, when the image capture and the traveling-directiondetection are to be finished, the controller 500 ends the flow.

FIGS. 11A and 12A schematically illustrate a state in which a hostvehicle V on which the detecting device 1 is mounted is traveling whilefollowing a vehicle W ahead. FIGS. 11B, 11C, 12B, and 12C eachschematically illustrate one example of an image represented bymultiple-exposure image data that is acquired.

FIG. 11A illustrates an example in which the specific target object is alicense plate. When the imaging device 100 images the license plate ofthe vehicle W in accordance with the drive illustrated in FIG. 7A,multiple-exposure image data illustrated in FIG. 11B is acquired.According to this drive, the later the image data is acquired, thehigher the lightness of the image is. In the multiple-exposure imagedata illustrated in FIG. 11B, the size of the image of the license platedecreases gradually in a time series. The controller 500 detects therelative traveling direction, based on the lightness of the image of thelicense plate and a change in the size of the image. In this example, itcan be understood that the relative traveling direction of the hostvehicle V with respect to the vehicle W is backward. It can also beunderstood from this that the relative speed of the host vehicle V isdecreasing.

FIG. 11C illustrates another example in which the specific target objectis a license plate. When the imaging device 100 images the license platein accordance with the drive illustrated in FIG. 7C, themultiple-exposure image data illustrated in FIG. 11C is acquired.According to this drive, the later the image data is acquired, the lowerthe lightness of the image is. In the multiple-exposure image dataillustrated in FIG. 11C, the size of the image of the license platedecreases gradually in a time series. In this example, it can beunderstood that the relative traveling direction of the host vehicle Vwith respect to the vehicle W is backward. It can also be understoodfrom this that the relative speed of the host vehicle V is decreasing.

FIG. 12A illustrates an example in which the specific target object isbrake lights. When the imaging device 100 images the brake lights of thevehicle W in accordance with the drive illustrated in FIG. 7A, themultiple-exposure image data illustrated in FIG. 12B is acquired.According to this drive, the later the image data is acquired, thehigher the lightness of the image is. In the multiple-exposure imagedata illustrated in FIG. 12B, the size of the image of the brake lightsdecreases gradually in a time series. In this example, it can beunderstood that the relative traveling direction of the host vehicle Vwith respect to the vehicle W is backward. It can also be understoodfrom this that the relative speed of the host vehicle V is decreasing.

FIG. 12C illustrates another example in which the specific target objectis brake lights. When the imaging device 100 images the brake lights inaccordance with the drive illustrated in FIG. 7C, the multiple-exposureimage data illustrated in FIG. 12C is acquired. According to this drive,the later the image data is acquired, the lower the lightness of theimage is. In the multiple-exposure image data illustrated in FIG. 12C,the size of the image of the license plate decreases gradually in a timeseries. In this example, it can be understood that the relativetraveling direction of the host vehicle V with respect to the vehicle Wis backward. It can also be understood from this that the relative speedof the host vehicle V is decreasing. Also, when the brake lights areused as the specific target object, the relative traveling direction andthe relative speed may be detected using the largeness/smallness of thegap between the left and right brake lights in the multiple-exposureimage data.

Although, in the above-described example, the controller 500 startsdetection of the traveling direction upon detecting the feature of thespecific target object, the present disclosure is not limited thereto.For example, the controller 500 may constantly detect the travelingdirection while the engine of the vehicle is running. Alternatively, thecontroller 500 may detect the traveling direction at regular intervalsor may start detection of the traveling direction upon entering ahighway. In addition, the controller 500 may detect the travelingdirection upon a change in internal control information about gearshifting or the like.

The license plate and the brake lamps are examples of the specifictarget object. The specific target object can be any target objecthaving dimensions specified by a standard. The specific target objectcan be, for example, a dedicated marker used for measuring the speed ofa vehicle. It is desirable that, when the relative traveling directionand the relative speed are to be measured, the imaging device 100 beinstalled at a front side or rear side of the vehicle. This makes itpossible to suppress error during measurement. Also, when an imagingdevice 100 having a wide imaging range is installed, for example, on aside mirror or a headlight of the vehicle, it is possible to minimizeinfluences of the arrangement on the shape and design of the vehicle.The “wide imaging range” means that, for example, the angle of view islarge.

<1.4. Specific Example 2 of Operation of Detecting Device>

Specific example 2 of the operation of the detecting device 1 will bedescribed with reference to FIGS. 13A to 13C.

FIG. 13A schematically illustrates a state in which the host vehicle onwhich the detecting device 1 is mounted is traveling while imaging aroad sign S. FIGS. 13B and 13C schematically illustrate an imagerepresented by pieces of image data included in multiple-exposure imagedata that is acquired.

In this specific example, the detecting device 1 detects the absolutetraveling direction of the host vehicle by imaging a stationary body.The stationary body is, for example, a road sign S installed along theroad. The road sign S acts as a specific target object. When the imagingdevice 100 images the road sign S in accordance with the driveillustrated in FIG. 7A, the multiple-exposure image data illustrated inFIG. 13B or 13C is acquired. According to this drive, the later theimage data is acquired, the higher the lightness of the image is. In themultiple-exposure image data illustrated in FIG. 13B, the lightness atthe right end of the image, that is, the lightness of a rearmost imageof the road sign S relative to the vehicle is the highest, and thelightness of the front most image is the lowest. This means that thehost vehicle is traveling in the forward direction.

On the other hand, in the multiple-exposure image data illustrated inFIG. 13C, the lightness at the left end of the image, that is, thelightness of the front most image of the road sign S relative to thevehicle is the highest, and the lightness of the rearmost image is thelowest. This means that the host vehicle is traveling backward.

As described above, the detecting device 1 can detect the absolutetraveling direction of the host vehicle, based on the multiple-exposureimage data of the road sign S. In this example, when the installationplace of the road sign S is considered, it is desirable that the imagingdevice 100 be installed on a side surface of the vehicle.

<1.5. Specific Example 3 of Operation of Detecting Device>

Specific example 3 of the operation of the detecting device 1 will bedescribed with reference to FIG. 14.

FIG. 14 illustrates one example of a processing flow for detecting therelative or absolute traveling direction and the speed of a vehicle andcontrolling braking and accelerating of the vehicle based on thedetection results.

When the controller 500 detects a feature of a specific target object,like that described above (step S200), the process proceeds to a processfor detecting the traveling direction and the speed.

The controller 500 starts detection of the traveling direction and thespeed (step S210).

The controller 500 acquires a multiple-exposure image data, for example,in a frame for direction detection. As in step S120 in the processingflow illustrated in FIG. 10, the controller 500 measures degrees of adisplay attribute in respective first and second image data in themultiple-exposure image data to detect the traveling direction (stepS220).

The distance measuring unit 600, for example, a TOF, measures a distanced from the host vehicle to the specific target object, for example, inresponse to a start instruction from the controller 500. The controller500 receives the distance d from the distance measuring unit 600 (step230).

The controller 500 detects the speed by using an interval m ofspecific-target-object images represented by the first and second imagedata included in the multiple-exposure image data, the distance d fromthe host vehicle to another vehicle, and an exposure interval t betweena first exposure period and a second exposure period (step S240). Thespecific target object is, for example, a license plate. The distance dfrom the host vehicle to the other vehicle is, to be precise, thedistance from the distance measuring unit 600 to the license plate ofthe other vehicle. The speed is the speed of the host vehicle withrespect to a vehicle traveling in the surroundings.

The interval of the specific-target-object images represented by thefirst and second image data included in the multiple-exposure image datacan be represented by, for example, the interval of feature points inthe respective specific-target-object images. The feature point is, forexample, an edge of the specific target object. The controller 500 candetect the edge of the specific target object, for example, by using aknown edge-detection scheme. The controller 500 computes an interval Ibetween the edges of the specific target objects in the pieces of imagedata.

The exposure interval t between the first exposure period and the secondexposure period is illustrated, for example, in FIG. 7A. The exposureinterval t illustrated in FIG. 7A corresponds to a period from the endof the first exposure period to the end of the second exposure period.In other words, the exposure interval t corresponds to an interval oftimings at which the control signal V2 goes from high to low.

For example, when a license plate is imaged with the general multipleexposures, images of the license plate are multiplexed along thetraveling direction of the vehicle. Thus, with only the information, itis not possible to distinguish whether the host vehicle is approachingthe surrounding vehicle or is moving away from the surrounding vehicle.In this specific example, in step S220, information indicating thetraveling direction of the host vehicle is obtained. Therefore, thedetecting device 1 can obtain information including the magnitude of thespeed of the host vehicle and the direction thereof. That is, thedetecting device 1 can obtain an accurate speed vector of the hostvehicle.

The detecting device 1 transmits the information indicating thetraveling direction and the speed to the ECU 800 via the imagetransmission IF 400.

The ECU 800 controls braking and accelerating of the vehicle, based onthe information indicating the traveling direction and the speed, theinformation being received from the detecting device 1 (step S250). Forexample, when travel assistance corresponding to autonomous drivinglevel 0 or 1 is assumed, the ECU 800 controls braking, for example, whenthe gap (the distance d) to the surrounding vehicle becomes apredetermined threshold or less, or when the speed exceeds apredetermined threshold. Specifically, for example, when it is detectedthat the distance to another vehicle traveling ahead has become smallerthan a predetermined value, the brake of the host vehicle may beactuated so as to increase the distance to the other vehicle, or controlmay be performed so as to actuate the gas pedal of the other vehicle.Also, for example, when it is detected that the distance to anothervehicle traveling ahead has become larger than a predetermined value,the gas pedal of the host vehicle may be actuated so as to reduce thedistance to the other vehicle, or control may be performed so as toactuate the brake of the other vehicle. The autonomous driving levelsmean automation references from levels 0 to 4 specified by the JapaneseGovernment. For example, when autonomous driving or fully autonomousdriving corresponding to autonomous driving levels 2 to 4 is assumed,the ECU 800 controls braking, for example, based on the distance dbetween the host vehicle and the surrounding vehicle, information of animaged road sign, road traffic information, and map information. The mapinformation is, for example, GPS information.

According to the vehicle-traveling control system 1000, traveling of thehost vehicle and another vehicle can be controlled based on thedetection results of the traveling direction and the speed. For example,the detection results obtained by the host vehicle can be used fortraveling control of the host vehicle. Alternatively, the detectionresults obtained by the host vehicle can be used for traveling controlof another vehicle. The ECU 800 may also be adapted to generate a signalfor controlling the braking and accelerating of the vehicle based on theinformation indicating the traveling direction and the speed, theinformation being received from the detecting device 1, and to outputthe signal to outside. In this case, for example, the autonomous-drivingcontrol device in the host vehicle or the other vehicle may receive thesignal and control driving of the host vehicle or the other vehicle.

The controller 500 determines whether or not the image capture is to becontinued (step S260). For example, the controller 500 determines thatthe image capture is to be continued, when the engine is running, anddetermines that the image capture is to be stopped, when the engine isstopped. When the controller 500 determines that the image capture is tobe continued, the process returns to step 200 again.

As described above, according to the vehicle-traveling control system1000 including the detecting device 1 and the ECU 800, avehicle-traveling control system supporting traveling assistance,autonomous driving, and fully autonomous driving and a vehicle on whichthe vehicle-traveling control system is mounted are provided.

Although an example in which the distance measuring unit 600 measuresthe distance d from the host vehicle to the target object has beendescribed in step S230, the present disclosure is not limited thereto.The controller 500 can also calculate the distance d by analyzing themultiple-exposure image data.

The controller 500 can calculate the distance d from the host vehicle toanother vehicle, based on a result of comparison between the actual sizeof a specific target object and the size of the specific target objectin the multiple-exposure image data. The actual size of the specifictarget object is pre-specified by a standard. The size s of the specifictarget object in the multiple-exposure image data at the distance d isdetermined based on the standard and various parameters related to theimaging device 100 and the optical system 200. The correspondencerelationship between the distance d and the size s of the specifictarget object can be, for example, pre-stored in the program memory 530.For example, based on the correspondence relationship, the controller500 can compute the distance d from the host vehicle to another vehicle.According to this configuration, since the distance measuring unit 600becomes unnecessary, the vehicle-traveling control system 1000 can besimplified, and the system cost can be reduced. Also, although, herein,all processes are performed in a time series, the order of theindividual processes can be changed, or the individual processes can beperformed in parallel. For example, the traveling-direction detectionand the speed detection can also be performed in parallel withsequential image captures. In this case, all of data resulting from theimage captures may be utilized or may be utilized after thinning onlydata required for computation.

<1.6. Specific Example 4 of Operation of Detecting Device>

Specific example 4 of the operation of the detecting device 1 will bedescribed with reference to FIG. 15.

FIG. 15 illustrates one example of a processing flow for detecting thetraveling direction, the speed, and the acceleration of a vehicle andcontrolling braking and accelerating of the vehicle based on thedetection results.

The processing flow illustrated in FIG. 15 differs from the processingflow illustrated in FIG. 14 in that the processing flow illustrated inFIG. 15 includes a process for detecting an acceleration. The differentpoint will be mainly described below.

The controller 500 detects the traveling direction by measuring thedegrees of a display attribute of target-object images represented byfirst and second image data, as in step S120 in the processing flowillustrated in FIG. 10. In addition, the controller 500 measures thedegrees of the display attribute of the target-object image representedby the second image data and a target-object image represented by thirdimage data to detect the traveling direction (step S320). The first tothird image data are a group of image data that are continuous in a timeseries. The first and second image data are typically a set of twoadjacent pieces of image data whose exposure periods are adjacent toeach other, and the second and third image data are typically a set oftwo adjacent pieces of image data whose exposure periods are adjacent toeach other. However, the two pieces of image data do not have to be aset of two pieces of image data that are continuous in a time series.For example, of the first to fourth pieces of continuous image data, aset of the first and third image data and a set of the second and fourthimage data may also be selected.

The controller 500 obtains speed 1 including information on themagnitude and the direction, based on the set of first and second imagedata. In this case, the speed is represented by a speed vector. Thecontroller 500 further obtains speed 2, based on the set of second andthird image data. The controller 500 computes the acceleration bymeasuring the amount of change in speeds 1 and 2 per unit time (step340).

The detecting device 1 transmits information indicating the travelingdirection, speeds 1 and 2, and the acceleration to the ECU 800 via theimage transmission IF 400.

The ECU 800 can control the braking and the accelerating of the vehicle,based on at least one of the pieces of information indicating thetraveling direction, speeds 1, 2, and the acceleration, the informationbeing received from the detecting device 1.

According to this specific example, the braking and the accelerating ofa vehicle can be controlled using the measured speed and acceleration.Thus, it is possible to continuously recognize the traveling state ofthe host vehicle, so that safer control can be performed.

A more detailed algorithm for detecting the speed and the accelerationof a vehicle will be described with reference to FIGS. 16A to 20. Beforethe algorithm in the present disclosure is described, a description willbe given of an algorithm in a reference example.

FIG. 16A illustrates functional blocks of a controller in the referenceexample. FIG. 16B schematically illustrates an image in a frame t−1.FIG. 16C schematically illustrates an image in a frame t that followsthe frame t−1. FIG. 16D schematically illustrates motion of a specifictarget object, the motion being obtained from pieces of image data inthe frames t−1 and t.

The controller in the reference example includes at least two framememories 51A and 51B, a motion-vector detecting unit 52, an objectdetecting unit 53, and a speed detecting unit 54. An algorithm fordetecting the speed is realized by, for example, a combination of amicrocontroller and software. Each of the functional blocks illustratedin FIG. 16A is illustrated in a unit of functional block, not in a unitof hardware. The pieces of image data corresponding to the respectiveframes t−1 and t are output from an imaging device 50. The image datacorresponding to the frame t−1 is temporarily held in the frame memory51A. The image data corresponding to the frame t is temporarily held inthe frame memory 51B.

The motion-vector detecting unit 52 reads the image data correspondingto the frame t from the frame memory 51A and reads the image datacorresponding to the frame t−1 from the frame memory 51B. Also, themotion-vector detecting unit 52 compares the values of the pieces ofimage data for each pixel to identify a pixel group in which the valuesof the pieces of image data have differences. In addition, based on theidentified pixel group, the motion-vector detecting unit 52 generates amotion vector signal indicating the motion of a specific target object.

Specifically, as illustrated in FIG. 16D, two pieces of image data arecompared with each other to thereby detect the direction of movement andthe amount of movement of a specific target object in the image.

The object detecting unit 53 reads the image data corresponding to theframe t from the frame memory 51A and detects a feature part of thespecific target object by using a known object-recognition algorithm.The specific target object is a target object used for image analysisfor speed sensing. As described above, the specific target object refersto, for example, on-road marking information, such as a white line or asign, or the license plate of another vehicle. Herein, a specific targetobject that is stationary may be referred to as a “static object”, and aspecific target object that is moving may be referred to as a “motioningobject”. The object detecting unit 53 detects a feature part of thespecific target object by using a common sensing scheme, such as shapedetection or edge detection.

The speed detecting unit 54 calculates at least one of a host-vehiclespeed, an another-vehicle speed, and a relative speed, based on a motionvector signal output from the motion-vector detecting unit 52 and adetection result output from the object detecting unit 53. When aspecific target object exists at a portion having a motion indicated bythe motion vector signal, the speed detecting unit 54 detects the amountof movement thereof as a speed. For example, the speed detecting unit 54first calculates the speed of the host vehicle, based on the size of theon-road marking information in the image and the amount of movementthereof. Next, the speed detecting unit 54 calculates the relative speedof the host vehicle or the relative speed of another vehicle, based onthe speed of the host vehicle, the size of the license plate of theother vehicle, and the amount of movement of the license plate.

FIG. 16E illustrates a processing flow for an algorithm in the referenceexample for detecting a speed. By using image data for a frame t andimage data for a frame t−1, the motion-vector detecting unit 52calculates motion vectors v(i, j) at all pixels P(i, j) in a presetregion R in the image data for the frame t (steps S1010 and S1011). Theobject detecting unit 53 determines whether or not a specified specifictarget object exists in the region R in the image data for the frame t(steps S1012 and S1013). When a static object exists in detectedspecific target objects (Yes in step S1014), the speed detecting unit 54calculates a speed V₁ of the host vehicle, based on an in-image size andthe motion vector v(i, j) of the static object (step S1015). When anymotioning object exists in the detected specific target objects afterthe speed V₁ of the host vehicle is calculated (Yes in step S1016), thespeed detecting unit 54 calculates speeds V_(2i) of all motioningobjects, based on the speed V₁ of the host vehicle, and in-image sizesand the motion vectors v(i, j) of the motioning objects (steps S1017 andS1018).

According to this reference example, the speed V₁ of the host vehicle isfirst determined, and then the speeds V_(2i) of the motioning objectsare determined. Thereafter, the relative speed of the host vehicle orthe relative speed of another vehicle is determined based on the speedV₁ of the host vehicle and the speeds V_(2i) of the motioning objects.

Next, a description will be given of an algorithm for detecting a speedand an acceleration by using multiple-exposure image data. FIG. 17illustrates functional blocks in the controller 500. FIG. 18 illustratesa processing flow for an algorithm for detecting a speed and anacceleration. FIG. 19A illustrates one example of an image inmultiple-exposure image data.

The controller 500 includes a frame memory 910, a bidirectional-vectorcalculating unit 920, an object detecting unit 930, and aspeed/acceleration determining unit 940. The algorithm for detecting thespeed and the acceleration is realized by, for example, a combination ofthe microcontroller 550 illustrated in FIG. 1 and software. Each of thefunctional block illustrated in FIG. 17 is illustrated in a unit offunctional block, not in a unit of hardware. The software can be, forexample, a module that constitutes a computer program for executing aspecific process corresponding to each functional block. Such a computerprogram can be stored in the program memory 530 illustrated in FIG. 1.The microcontroller 550 can read a command from the program memory 530and sequentially execute each process.

The frame memory 910 corresponds to the working memory 540 illustratedin FIG. 1 or 2. The frame memory 910 may have a capacity that is capableof holding an image data for one frame. The frame memory 910 holds imagedata for a frame t which is multiple-exposure image data.

The bidirectional-vector calculating unit 920 reads the image data forthe frame t from the frame memory 910. Also, the bidirectional-vectorcalculating unit 920 detects a feature part of a specific target objectfrom the image data for the frame t. When the specific target object ismoving in the period of the frame t, the feature part of the specifictarget object is detected from a plurality of portions in the image datafor the frame t. The bidirectional-vector calculating unit 920 detectsthe motion of the specific target object from the positions of featureparts at the plurality of portions in the image.

FIG. 19A illustrates motion vectors calculated by thebidirectional-vector calculating unit 920. The directions of the motionvectors illustrated in FIG. 19A are not uniquely specified. Herein, amotion vector whose direction is not uniquely specified is referred toas a “bidirectional vector v_(bd)(i, j)”.

As illustrated in FIG. 16D, according to the reference example, sincepieces of image data for two frames at different time points arecompared with each other, the feature parts of a specific target objectexist in different frames, so that the directions of motion vectors canbe uniquely determined. In contrast, when the multiple-exposure imagedata is used, the feature parts of the specific target object obtainedat different time points exist in the same frame. Thus, the directionsof motion vectors cannot be uniquely determined.

When attention is paid to a certain portion of a vehicle in the imageillustrated in FIG. 19A, two images that are similar to the portionappear in the vicinity thereof. Although a movement trace of the vehiclecan be recognized from the positions of the series of images, theanteroposterior relationship of the times at which the images at twoopposite ends of the movement trace were acquired cannot be determined.

When the multiple-exposure image data is used, it is necessary to varyan imaging condition in order to identify the start point and the endpoint of the series of images. For example, the exposure time when afirst image is acquired may further be increased. This makes it possibleto increase the brightness of the first image and makes it possible toidentify the start point of the series of images. Eventually, it ispossible to obtain bidirectional vectors v_(bd)(i, j) and the directionsthereof.

The bidirectional-vector calculating unit 920 calculates bidirectionalvectors v_(bd)(i, j) with respect to pixels P(i, j) by using a frame t(step S1110). The bidirectional-vector calculating unit 920 performs theprocess in S1110 until bidirectional vectors v_(bd)(i, j) are calculatedwith respect to all pixels P(i, j) in a preset region R (step S1111).The object detecting unit 930 determines whether or not a specifictarget object exists in the preset region R in the frame t, for example,by using edge detection (step S1120). The object detecting unit 930reads image data for the frame t from the frame memory 910. The objectdetecting unit 930 detects a feature part of each specific target objectby using a typical sensing scheme, such as shape detection or edgedetection.

FIG. 19B illustrates an image represented by multiple-exposure imagedata resulting from image capture with the sensitivity being increasedfor only the last exposure of multiple exposures. In FIG. 19B, the lastvehicle image acquired is NI. The brightness of an edge of a featurepart in the last vehicle image acquired is higher than the brightness ofthe edges of the feature parts in the other images. The object detectingunit 930 senses the brightnesses of edges of feature parts in the imagesof the vehicle. The object detecting unit 930 performs a determinationas to whether or not a specific target object exists on all regions R(step S1121). When this determination indicates that a static object anda motioning object exist in any of the regions R, the object detectingunit 930 may identify the presence of both. Also, when a plurality ofmotioning objects exists in any of the regions R, the object detectingunit 930 may identify the presence of the plurality of motioningobjects.

When the object detecting unit 930 detects a static object (Yes in stepS1122), the bidirectional-vector calculating unit 920 calculatesbidirectional vectors v_(bd)(i, j), based on the positions of featureparts of the specific target object detected by the object detectingunit 930. In addition, the bidirectional-vector calculating unit 920compares the brightnesses of edges of the feature parts of the specifictarget object with each other to identify the last image acquired anddetermines the directions of the bidirectional vectors v_(bd)(i, j). Abidirectional vector v_(bd)(i, j) whose direction is uniquely specifiedis referred to as a “vector v_(d)(i, j)”.

FIG. 19C illustrates a motion vector when attention is paid to one pointon the license plate of a vehicle. A vector denoted by a dashed linerepresents an entire amount-of-movement vector v(i, j), which is a totalamount of movement in a frame. Vectors denoted by solid lines eachrepresent a vector v_(d)(i, j), which is an amount of movement betweenexposures of multiple exposures. Based on the total of the vectorsv_(d)(i, j), the bidirectional-vector calculating unit 920 calculates anentire amount-of-movement vector v(i, j) (step S1130). Thebidirectional-vector calculating unit 920 performs the process in S1130until entire amount-of-movement vectors v(i, j) are calculated withrespect to all bidirectional vectors v_(bd)(i, j) (step S1131). Thebidirectional-vector calculating unit 920 outputs bidirectional vectorsignals including the entire amount-of-movement vector v(i, j) of eachstatic object to the speed/acceleration determining unit 940.

Based on the bidirectional vector signals from the bidirectional-vectorcalculating unit 920 and the detection result from the object detectingunit 930, the speed/acceleration determining unit 940 calculates thespeed and the acceleration of the vehicle. Based on the size of thestatic object in the image and the entire amount-of-movement vector v(i,j) of the static object, the speed/acceleration determining unit 940calculates a host-vehicle speed V₁. In addition, the speed/accelerationdetermining unit 940 calculates a host-vehicle acceleration A₁, based onthe amount of changes in the vectors v_(d)(i, j) belonging to the entireamount-of-movement vector v(i, j) (step S1140).

When the object detecting unit 930 detects a motioning object (Yes instep S1150), the bidirectional-vector calculating unit 920 traces backbidirectional vectors v_(bd)(i, j) on the detected motioning object,based on the result of the motioning object detection performed by theobject detecting unit 930, and calculates vectors v_(d)(i, j) whosedirections are determined. In addition, based on the total of thevectors v_(d)(i, j), the bidirectional-vector calculating unit 920calculates an entire amount-of-movement vector v(i, j) as a motionvector of the motioning object (step S1160). The bidirectional-vectorcalculating unit 920 performs the process in S1160 until entireamount-of-movement vectors v(i, j) are calculated with respect to allbidirectional vectors v_(bd)(i, j) (step S1161). Thebidirectional-vector calculating unit 920 outputs bidirectional vectorsignals further including the entire amount-of-movement vectors v(i, j)of the motioning objects to the speed/acceleration determining unit 940.

The speed/acceleration determining unit 940 detects the speed, based onthe amount of motion of the motioning object. More specifically, thespeed/acceleration determining unit 940 calculates the speed and theacceleration of the vehicle by using the amount of motion of themotioning object, the amount being determined based on the bidirectionalvector signals from the bidirectional-vector calculating unit 920 andthe detection result from the object detecting unit 930. Based on thehost-vehicle speed V₁ and the in-image size and the entireamount-of-movement vector v(i, j) of the motioning object, thespeed/acceleration determining unit 940 calculates a motioning-objectspeed V_(2i), that is, the speed of another vehicle. In addition, basedon the amount of changes in the vectors v_(d)(i, j) belonging to theentire amount-of-movement vector v(i, j) of the motioning object, thespeed/acceleration determining unit 940 calculates an accelerationA_(2i) of the other vehicle (step S1170). The speed/accelerationdetermining unit 940 performs the process in S1170 untilmotioning-object speeds V_(2i) and moving body accelerations A_(2i) arecalculated with respect to all the motioning objects detected by theobject detecting unit 930 (step S1171).

The speed/acceleration determining unit 940 can determine the relativespeed of the host vehicle or another vehicle, based on the calculatedhost-vehicle speed V₁ and another-vehicle speed V_(2i). Also, thespeed/acceleration determining unit 940 can determine the relativeacceleration of the host vehicle or another vehicle, based on thecalculated host-vehicle acceleration A₁ and another-vehicle accelerationA_(2i).

FIG. 20 illustrates another example of the functional blocks in thecontroller 500 that detects a speed and an acceleration by using themultiple-exposure image data. As illustrated, after a process in whichthe object detecting unit 930 senses a specific target object, thebidirectional-vector calculating unit 920 may execute a process forgenerating bidirectional vector signals.

In this manner, it is possible to detect the speed and the accelerationof a specific target object by using the multiple-exposure image data.Thus, for example, in driving control on the braking, accelerating, orthe like of a vehicle, it is expected that the amount of computation fordetermining details of the control can be significantly reduced. Also,it is possible to reduce the number of frame memories that are used.

In the reference example, the interval of measuring a specific targetobject is limited by the reading speed of the image sensor. When themultiple-exposure image data is used, the interval of measuring aspecific target object is defined by the interval of exposures ofmultiple exposures. As a result, it is possible to improve themeasurement accuracy. Also, since the amount of movement of eachspecific target object is small, the measurement accuracy is alsoexpected to improve. In addition, a computational area required for thespeed sensing can be narrowed down, and the amount of computation can bereduced.

Also, in this description, the speed is determined by calculating anentire amount-of-movement vector v(i, j) as a motion vector of amotioning object, based on the total of vectors v_(d)(i, j). However,for example, the speed changes significantly during right or left turnor during full turn. In such a case, the speed and the acceleration maybe calculated from each vector v_(d)(i, j). A subsequent operation maybe predicted or driving control of the host vehicle or another vehiclemay be performed, based on the calculated speed and acceleration.

Although, in the above-described embodiment, the sensitivity of the lastexposure of the multiple exposures is increased to perform imagecapture, the present disclosure is not limited thereto. For example, thesensitivity of the last exposure of the multiple exposures may bereduced to perform image capture, or the sensitivity of the firstexposure of multiple exposures may be varied to perform image capture.In addition, of the multiple exposures, the sensitivity of the exposurein a predetermined order, for example, the second exposure, may bevaried to perform image capture. Also, the number of exposures in whichthe sensitivity is varied does not have to be one, and the sensitivitiesof a plurality of exposures may be made different from the sensitivityof other exposures. When the sensitivities of some exposures are madedifferent from the sensitivity of other exposures, the anteroposteriorrelationship of images corresponding to the respective exposures can berecognized in an multiple-exposure image. In addition, When thesensitivities of other exposures are aligned to a certain sensitivity,the lightnesses of images corresponding to respective exposures becomesubstantially the same, thus making it easy to detect feature points inthe images.

<1.7. Specific Example 5 of Operation of Detecting Device>

Specific example 5 of the operation of the detecting device 1 will bedescribed with reference to FIGS. 21A to 21C.

FIG. 21A schematically illustrates a state in which a drone Don whichthe detecting device 1 is mounted is flying. FIGS. 21B and 21C eachschematically illustrate one example of an image represented bymultiple-exposure image data that is acquired.

The detecting device 1 can also be desirably mounted on not only avehicle but also an aircraft. The detecting device 1 is used as a speedsensing device for any moving body. An example in which the detectingdevice 1 is mounted on the drone D will be described below.

The drone D includes the detecting device 1. The imaging device 100 inthe detecting device 1 images a dedicated marker for measurement, thededicated marker being attached to a utility pole. The detecting device1 acquires multiple-exposure image data including the dedicated markerand analyzes the multiple-exposure image data to thereby acquire, forexample, speed information. FIGS. 21B and 21C each indicate one exampleof an image represented by the multiple-exposure image data.

When the imaging device 100 images the dedicated marker in accordancewith the drive illustrated in FIG. 7A, for example, the imageillustrated in FIG. 21B or 21C is acquired. According to the driveillustrated in FIG. 7A, the later the image is acquired, the higher thelightness thereof is. In the image illustrated in FIG. 21B, thelightness of the dedicated marker at the right end, that is, thelightness of the image of a rearmost dedicated marker relative to thedrone D is the highest, and the lightness of the image of a front mostdedicated marker is the lowest. The front of the drone D means theimmediately front direction of the drone D. The image illustrated inFIG. 21B means that the drone D is flying frontward. In the imageillustrated in FIG. 21C, the lightness at the right end, that is, thelightness of the image of a front most dedicated marker relative to thedrone D is the highest, and the lightness of the image of a rearmostdedicated marker is the lowest. The image illustrated in FIG. 21B meansthat the drone D is flying backward.

The flight of the drone D may be controlled based on the detected speedinformation. For example, mounting the detecting device 1 and anartificial intelligence (AI) on the drone D allows the drone D toperform unmanned autonomous flight.

Also, although an example of traveling-direction detection for anaircraft has been described above in conjunction with an example of thedrone D, traveling-direction detection and speed detection using asimilar scheme are possible for various moving bodies, such as thehuman, industrial control equipment, and autonomous robots.

Second Embodiment

In the present embodiment, an operation example for detecting a speedwill be mainly described.

A detecting device 2 according to the present embodiment can include,for example, the hardware configuration illustrated in FIG. 1 or 2.Hence, the description of blocks in the detecting device 2 is omitted.

<2.1. Specific Example 1 of Operation of Detecting Device 1>

Specific example 1 of the operation of the detecting device 2 will bedescribed with reference to FIGS. 22A to 25.

FIG. 22A schematically illustrates a state in which a host vehicle onwhich the detecting device 2 is mounted is traveling while imaging aroad sign S. FIGS. 22B to 22D each schematically illustrate one exampleof an image in multiple-exposure image data that is acquired.

As illustrated in FIG. 22A, the detecting device 2 mounted on a hostvehicle, which is a moving body, images the road sign S, which is astationary body. The detecting device 2 detects an absolute speed of thevehicle, based on the acquired multiple-exposure image data. When theimaging device 100 performs the general multiple-exposure image capturein accordance with the drive illustrated in FIG. 6A, for example, theimage illustrated in FIG. 22B is acquired.

When the imaging device 100 performs multiple-exposure image capturewhile performing sensitivity modulation in accordance with the driveillustrated in FIG. 7A or 8A, for example, the image illustrated in FIG.22C is acquired. When the imaging device 100 performs multiple-exposureimage capture while performing sensitivity modulation in accordance withthe drive illustrated in FIG. 7C or 8C, for example, the imageillustrated in FIG. 22D is acquired.

In this specific example, detection of the absolute speed of the hostvehicle can be realized using the general multiple exposure. In thisspecific example, since the traveling direction of the host vehicle isnot detected, it is not necessary to perform multiple exposures viasensitivity modulation.

FIG. 23A schematically illustrates a state in which the host vehicle onwhich the detecting device 2 is mounted is traveling while imaging awhite line on a road. FIG. 23B schematically illustrates one example ofan image that is acquired. FIG. 24A schematically illustrates a state inwhich the host vehicle on which the detecting device 2 is mounted istraveling while imaging a dedicated marker for measurement, thededicated marker being attached to a utility pole. FIG. 24Bschematically illustrates one example of an image represented bymultiple-exposure image data that is acquired.

FIGS. 23B and 24B each illustrate one example of an image represented bymultiple-exposure image data when the imaging device 100 performs thegeneral multiple-exposure image capture in accordance with the driveillustrated in FIG. 6A. A specific target object for performing speedmeasurement may be an on-road installation whose size has beenstandardized. The specific target object is, for example, a road sign S,a white line, a utility-pole sign board, or a traffic light. Thespecific target object may also be the license plate or lamps of avehicle, like those described above. In addition, the specific targetobject may be a dedicated marker whose size has been standardized. Amarker having a plurality of markers arranged in a vertical directionmay be used as the dedicated marker. With such a dedicated marker, evenwhen the vehicle moves forward, the amount of distortion in an image issmall, and measurement error is less likely to occur.

FIG. 25 illustrates one example of a processing flow for detecting anabsolute speed based on multiple-exposure image data and controlling thebraking and accelerating of a vehicle based on the absolute speed.

The processing flow for detecting the absolute speed is basically thesame as the processing flow illustrated in FIG. 14. However, step S220for detecting the traveling direction is omitted.

As described in the first embodiment, in step S230, the distance d fromthe host vehicle to the road sign S may be obtained by the distancemeasuring unit 600 or may be obtained by the controller 500 performinganalysis on the multiple-exposure image data. The distance measuringunit 600 is, for example, a TOF sensor.

FIG. 26A schematically illustrates one example of an image representedby multiple-exposure image data acquired by a vehicle that is travelingat a side closer to the road sign S in FIG. 24A. FIG. 26B schematicallyillustrates one example of an image represented by multiple-exposureimage data acquired by a vehicle that is traveling at a side fartherfrom the road sign S in FIG. 24A.

The size of the road sign S in the multiple-exposure image data variesaccording to the distance d from the vehicle to the road sign S. Asdescribed above, the actual size of the specific target object has beenpre-specified by a standard. The size s of the specific target object inthe multiple-exposure image data at the distance d is determined basedon the standard and various parameters related to the imaging device 100and the optical system 200. The controller 500 can compute the distancefrom the host vehicle to the road sign S, based on a result ofcomparison between the actual size of the road sign S and the size ofthe road sign S in the multiple-exposure image data.

Reference is made to FIG. 25 again.

The controller 500 acquires multiple-exposure image data by performingthe general multiple-exposure image capture. The controller 500 acquiresmultiple-exposure image data, for example, illustrated in FIG. 22B anddetects the absolute speed of the vehicle by using the distance d, aninterval m of edges of the road sign S, and an interval t of twoadjacent control signals V2 (step S240).

Thereafter, the detecting device 2 transmits information indicating theabsolute speed to the ECU 800 via the image transmission IF 400.

The ECU 800 can control the braking and accelerating of the vehicle,based on the information indicating the absolute speed, the informationbeing received from the detecting device 2. As in the first embodiment,the ECU 800 can perform, for example, control corresponding toautonomous driving levels 0 to 4.

Although, in the above-described example, the controller 500 startsdetecting the vehicle speed upon detecting a feature of a specifictarget object, the present disclosure is not limited thereto. Forexample, the controller 500 may constantly detect the vehicle speedwhile the engine of the vehicle is running. Alternatively, thecontroller 500 may also detect the vehicle speed in only periods set atregular intervals. For example, the controller 500 may detect thevehicle speed only in the period of the frame for direction detection,the period being illustrated in FIG. 9D. Alternatively, the controller500 may detect the vehicle speed upon entering a highway or may detectthe vehicle speed upon a change in internal control information aboutgear shifting or the like.

When the detecting device 2 is to measure the absolute speed, theimaging device 100 may be installed on a side surface of the vehicle.This makes it possible to suppress error during the measurement.

<2.2. Specific Example 2 of Operation of Detecting Device 2>

Specific example 2 of the operation of the detecting device 2 will bedescribed with reference to FIG. 27.

FIG. 27 illustrates one example of a processing flow for detecting anabsolute speed and an acceleration based on multiple-exposure image dataand controlling the braking and accelerating of the vehicle based on theabsolute speed and the acceleration.

The processing flow for detecting the speed and the acceleration isbasically the same as the processing flow illustrated in FIG. 15.However, step S320 for detecting the traveling direction is omitted.

In this specific example, the controller 500 computes the absolute speedand the acceleration of the vehicle, based on the multiple-exposureimage data (step S340). The absolute speed and the acceleration in thisspecific example respectively correspond to the speed and theacceleration obtained in step S340 illustrated in FIG. 15.

The ECU 800 can control the braking and accelerating of the vehicle,based on at least one of the pieces of information indicating theabsolute speed and the acceleration, the information being received fromthe detecting device 2. As in the first embodiment, the ECU 800 canperform, for example, control corresponding to autonomous driving levels0 to 4.

According to this specific example, it is possible to control thebraking and accelerating of the vehicle by using the measured absolutespeed and acceleration. Thus, it is possible to continuously recognizethe traveling state of the host vehicle. As a result, it is possible toperform safer control.

<2.3. Specific Example 3 of Operation of Detecting Device 2>

Specific example 3 of the operation of the detecting device 2 will bedescribed with reference to FIG. 28.

FIG. 28 illustrates one example of a processing flow for controlling thebraking and accelerating of a vehicle by further using the vehicle speedmeasured by the ECU 800.

The processing flow illustrated in FIG. 28 includes steps that areanalogous to those in the processing flow illustrated in FIG. 27. Theprocessing flow further includes at least one of step S370 in which thevehicle speed measured by the ECU 800 is fed back as an initial valuefor detection of the absolute speed and step S380 in which comparison ismade with the speed measured by the ECU 800 to correct the detectionspeed of the controller 500.

The ECU 800 can measure the vehicle speed independently from thedetecting device 2, for example, based on the rotational speed ofwheels. The ECU 800 transmits the measured vehicle speed to thecontroller 500 in the detecting device 2. The vehicle speed measured bythe ECU 800 is fed back to the controller 500, for example, through theCAN as an initial value for detection of the absolute speed. However,the feedback control can also be realized by a standard different fromthe CAN or by an individual standard.

The controller 500 can perform speed detection based on themultiple-exposure image data, by using an initial value determined basedon the speed information measured by the ECU 800 (step S370).

The controller 500 can correct the vehicle speed information detectedbased on the multiple-exposure image data, by using the speedinformation measured by the ECU 800. In other words, it is possible tocalibrate the detecting device 2 by using the vehicle speed measured bythe ECU 800 (step S380). The absolute speed detected by the controller500 is compared with the vehicle speed measured by the ECU 800. Theabsolute speed of the vehicle is corrected based on the vehicle speedmeasured by the ECU 800 and according to the comparison result. Both theabove-described feedback control and calibration may be applied, or oneof the feedback control and the calibration may be applied.

According to this specific example, close cooperation between the ECU800 and the detecting device 2 makes it possible to reduce offsetbetween individual mechanisms during control. In addition, it ispossible to realize high-speed feedback during speed control.

<2.4. Specific Example 4 of Operation of Detecting Device 2>

Specific example 4 of the operation of the detecting device 2 will bedescribed with reference to FIGS. 29 to 30D.

FIG. 29 illustrates one example of a processing flow for detecting aspeed based on multiple-exposure image data, further detecting thetraveling direction, and controlling the braking and accelerating. FIGS.30A, 30B, and 30C each schematically illustrate one example of an imagerepresented by multiple-exposure image data acquired via generalmultiple exposures.

FIG. 30C illustrates one example of an image represented bymultiple-exposure image data of a license plate, the data being acquiredwhen a vehicle traveling ahead and the host vehicle are close to eachother. FIG. 30D illustrates an image of a license plate, the image beingacquired when the vehicle traveling ahead and the host vehicle are farfrom each other.

In step S230, the distance measuring unit 600 may measure a distance dto a vehicle traveling ahead. Alternatively, the controller 500 maymeasure the distance d by using the above-described scheme to analyze,for example, the multiple-exposure image data illustrated in FIG. 30C.

The detecting device 2 according to this specific example obtains thespeed of the vehicle by analyzing multiple-exposure image data acquiredby the general multiple-exposure imaging (step S240). Specifically, thecontroller 500 acquires multiple-exposure image data, for example,illustrated in FIGS. 30A and 30B and detects the speed of the vehicle byusing the distance d, an interval m between edges of the specific targetobject, and an interval t of two adjacent control signals V2.

FIG. 30A illustrates one example of an image of a license plate, theimage being acquired by the general multiple-exposure imaging, and FIG.30B illustrates one example of an image of brake lamps, the image beingacquired by the general multiple-exposure imaging. According to thegeneral multiple-exposure imaging, images of a target object aresuperimposed in the traveling direction of the vehicle. Thus, adistinction cannot be made as to whether or not the host vehicle hasaccelerated to reduce the distance to a vehicle ahead or the hostvehicle has decelerated to increase the distance.

After obtaining the speed of the vehicle, the controller 500 accordingto this specific example detects the traveling direction of the vehicle(step S220). For example, it is possible to obtain informationindicating the traveling direction of the vehicle, by using thetraveling-direction measuring unit 700. The traveling-directionmeasuring unit 700 is, for example, a TOF sensor. The obtainedinformation is transmitted to the controller 500. Detecting thetraveling direction makes it possible to obtain the speed of thevehicle. The specific target object for speed detection is not limitedto a license plate and lamps and may be, for example, a marker for speeddetection, the marker being attachable to a vehicle.

As described above, in the present embodiment, when a target object tobe imaged is a stationary body, the controller 500 can detect theabsolute speed of the host vehicle. The stationary body is, for example,a road sign S. Alternatively, when a target object to be imaged isprovided on another moving body, the controller 500 can detect therelative speed of the host vehicle with respect to the other movingbody. The other moving body is, for example, a traveling vehicle, andthe target object to be imaged is a license plate.

The relative traveling direction and the relative speed can be used forthe braking and accelerating of the host vehicle or a vehicle that is ameasurement target. The absolute traveling direction and the absolutespeed, on the other hand, can be used for, for example, braking-modecontrol or failure detection of the host vehicle through use of thevalue of the absolute speed, in addition to being used for the brakingand accelerating of the host vehicle or a vehicle that is a measurementtarget. In addition, the absolute traveling direction and the absolutespeed can be used for determining a violation of a traffic regulationand so on.

The detecting device 2 may acquire the multiple-exposure image dataillustrated in FIG. 11B or 12B by performing multiple-exposure imagecapture via sensitivity modulation. The detecting device 2 may detectthe traveling direction by analyzing the multiple-exposure image data.

Multiple-exposure image data for detecting the speed of a vehicle andmultiple-exposure image data for detecting the traveling direction maybe acquired in different frames. Specifically, as illustrated in FIG.29, the speed is detected based on multiple-exposure image data acquiredin one frame (step S240). Thereafter, the traveling direction may bedetected based on multiple-exposure image data acquired in another frame(step S220). Alternatively, the speed and the traveling direction may bedetected based on multiple-exposure image data acquired in one frame(step S220). In addition, the order of the processes may be interchangedso as to make a change so that the speed is detected (step S240) afterthe traveling direction is detected (step S220). The detection of thespeed detection and the detection of the traveling direction may bealternately performed. The order of the processes can be selected in anyform, as long as it is optimum for the vehicle-traveling control system1000.

The detecting device 2 transmits information regarding the travelingdirection and the speed to the ECU 800 via the image transmission IF400. Based on the information regarding the traveling direction and thespeed, the information being received from the detecting device 2, theECU 800 can control the braking and accelerating of the vehicle (stepS250). As in the first embodiment, the ECU 800 can perform, for example,control corresponding to autonomous driving levels 0 to 4.

FIG. 31 illustrates one example of a processing flow for detecting aspeed and an acceleration based on multiple-exposure image data, furtherdetecting a traveling direction, and controlling braking/accelerating.

The processing flow illustrated in FIG. 31 includes the processing stepsillustrated in FIG. 27 and further includes step S320 for detecting thetraveling direction. According to this processing flow, the ECU 800 cancontrol the braking and accelerating of the vehicle, based on at leastone of the pieces of information about the traveling direction, thespeed, and the acceleration. It is possible to continuously recognizethe traveling state of the host vehicle, so that safer control can beperformed.

As described above, the multiple exposures via sensitivity modulation isnot necessarily required for detecting the vehicle speed. Also, forexample, the detecting device 2 may have a first mode in which thetraveling direction of a surrounding vehicle is detected using aplurality of pieces of brightness information in multiple-exposure imagedata and a second mode in which the relative speed of a surroundingvehicle relative to the host vehicle is calculated using a plurality ofpieces of brightness information. The detecting device 2 may also beadapted to alternately switch between the first and second modes everypredetermined period. The predetermined period may be, for example, acertain frame cycle. Also, the first mode and the second mode may alsobe switched when the speed or acceleration information changes, or whenbraking or a steering wheel operation is performed.

FIG. 32 illustrates one example of a processing flow for controlling thebraking/accelerating by using a vehicle speed measured by the ECU 800.

As illustrated in FIG. 32, step S320 for detecting the travelingdirection can also be added to the processing flow for detecting thespeed and the acceleration, the processing flow being illustrated inFIG. 28. According to this processing flow, the ECU 800 can control thebraking and accelerating of the vehicle, based on at least one of thepieces of information about the traveling direction, the speed, and theacceleration. Close cooperation between the ECU 800 and the detectingdevice 2 makes it possible to reduce offset among mechanisms duringcontrol and further makes it possible to perform high-speed feedbackduring speed control.

<2.5. Specific Example 5 of Operation of Detecting Device 2>

Specific example 5 of the operation of the detecting device 2 will bedescribed with reference to FIGS. 33A to 33C.

When the vehicle enters a curved road, the detecting device 2 cancompute a speed change relative to the inner circumference of the curveand a speed change relative to the outer circumference, based on themultiple-exposure image data, and can compute the vehicle's entry angle,based on the speed changes relative to the inner and outercircumferences.

FIG. 33A schematically illustrates a state in which the vehicle enters acurved road. FIG. 33B schematically illustrates one example of an imagerepresented by multiple-exposure image data acquired by imaging theoutside of the curved road when the vehicle enters the curved road, andFIG. 33C schematically illustrates one example of an image representedby multiple-exposure image data acquired by imaging the inside of thecurved road.

The vehicle-traveling control system 1000 according to this specificexample can control the braking/accelerating and steering of thevehicle, for example, in accordance with the processing flow illustratedin FIG. 25. As illustrated in FIG. 33A, for example, dedicated poles formeasuring the vehicle's entry angle are assumed to be installed oninside and outside shoulders of a curved road at predeterminedintervals. Dedicated markers for measurement which are analogous to themarker illustrated in FIGS. 24A and 24B may be installed on thededicated poles.

The controller 500 can sense the vehicle entry to the curve by usingsteering wheel operation, road traffic information, or map information.Upon being triggered by the sensing, the controller 500 starts measuringthe vehicle's entry angle (step S210). The controller 500 starts,specifically, computation for detecting a speed relative to the innercircumference of the curved road and a speed relative to the outercircumference of the curved road. Hereinafter, the speed relative to theinner circumference of the curved road is referred to as an “innercircumference speed”, and the speed relative to the outer circumferenceof the curved road is referred to as an “outer circumference speed”.

For example, the distance measuring unit 600 measures distances d_in andd_out from the host vehicle to the corresponding inside dedicated poleand outside dedicated pole. The controller 500 obtains the distancesd_in and d_out from the distance measuring unit 600 (step S230).

The controller 500 obtains multiple-exposure image data acquired byperforming multiple-exposure imaging on the inside pole. The controller500 detects the inner circumference speed of the host vehicle by usingan interval m_in between the dedicated poles in first and second imagedata in the multiple-exposure image data, an interval t_in between afirst exposure period and a second exposure period, and the distanced_in. Similarly, the controller 500 obtains multiple-exposure image dataacquired by performing multiple-exposure image capture on the outsidepoles. The controller 500 detects the outer circumference speed of thehost vehicle by using an interval m_out between the dedicated poles infirst and second image data in the multiple-exposure image data, aninterval t_out between a first exposure period and a second exposureperiod, and the distance d_out. In addition, the controller 500 computesthe angle of entering the curve, based on the outer circumference speedand the inner circumference speed of the host vehicle (step S240).

The detecting device 2 transmits the outer circumference speed and theinner circumference speed or information about the entry angle to theECU 800 via the image transmission IF 400. Based on those pieces ofinformation received from the detecting device 2 and other information,such as road traffic information or map information, the ECU 800 cancontrol the braking, accelerating, and steering of the vehicle (stepS250).

As described above, the information about the vehicle speed measured bythe ECU 800 may be used for calibrating the detecting device 2, and maybe set as an initial value used when the detecting device 2 computes theinner circumference and outer circumference speeds. Further, theinformation may be applied to both of them. In addition, information,other than vehicle speed, obtained by various sensors commonly used in avehicle-traveling control system may be fed back from the ECU 800 to thedetecting device 2 through a CAN, together with the vehicle speed. Thevarious sensors are, for example, a steering angle sensor and a yaw-ratesensor. The information other than the vehicle speed is, for example, asteering angle, a yaw rate, or an acceleration.

In this specific example, the imaging device 100 may be installed on aside surface of the vehicle. This makes it possible to suppress errorduring measurement.

According to this specific example, close cooperation between the ECU800 and the detecting device 2 makes it possible to reduce offset amongmechanisms during control and further makes it possible to realizehigh-speed feedback during vehicle control on braking, accelerating,steering, and so on.

<2.6. Examples of Host-Vehicle Position Estimation and Host-VehicleRoute Prediction Using Detecting Device 2>

In specific examples 1 to 5, the speed information detected by thedetecting device 2 has been described as being used only for controllingthe host vehicle. The present disclosure is not limited thereto, and thedetected speed information can be desirably used for, for example,accurate host-vehicle position estimation and host-vehicle routeprediction.

The host-vehicle position estimation and the host-vehicle routeprediction can utilize information about a speed, an acceleration, adistance to a target object, or the like that can be obtained by thedetecting device 2, information from various sensors used in thevehicle-traveling control system 1000, map information, inter-vehiclecommunication data, and data of communication between a vehicle and astationary body, for example, between a vehicle and a road sign.

With regard to the host-vehicle position estimation, the host-vehicleposition on a map can be estimated, for example, by measuring a distanceto a target object, such as a road sign, position information of atarget object in map information, and information about ameasured-distance between a target object and the host vehicle. Also,subsequent host-vehicle position estimation may be performed withrespect to the position information of a target object and theinformation about the measured distance between the target object andthe host vehicle, or the estimation of the host-vehicle position may becontinued by reflecting the host-vehicle traveling direction or speedinformation subsequently detected into the map information with respectto the host-vehicle position estimated at a certain point in time. Inaddition, the result of the host-vehicle position estimation may becorrected by measuring the distance to another target object and usingposition information of the other target object and the informationabout the distance between the target object and the host vehicle. Thegenerated map information may also be displayed, for example, on adisplay provided in a vehicle cabin or a portable terminal of a user.Also, as another embodiment, the motion state of the host vehicle aftera certain time passes can be predicted using information about thehost-vehicle position and speed information or acceleration informationmeasured by the above-described method. The host vehicle can also becontrolled according to the prediction result, surrounding trafficinformation obtained from the map information, and a destination. Ifboth vehicles can mutually predict routes, smooth traveling control on aplurality of vehicles can be performed utilizing a cloud server.

The speed information of a vehicle can be transmitted to a surroundingvehicle that is traveling in the surroundings. Transmitting the speedinformation detected by the detecting device 2 to a surrounding vehiclealso makes it possible to perform mutual control between vehicles.Controlling both vehicles at the same time makes it possible to reduce,for example, a braking time, a distance, and so on.

For example, communication between vehicles can be realized using apulse signal to which a recognition header is attached. However, thecommunication system is not limited to the inter-vehicle communication,and any system may be used as long as it is a scheme in which asurrounding vehicle can receive transmission data. The communication maybe unidirectional or may be bidirectional. Also, the communicationsystem is, for example, time division or wavelength multiplexing.

For example, headlight light can be utilized for the communication.Headlights are pulse-driven with a frequency that does not affectradiation to the surroundings, and another vehicle senses light of theheadlights to thereby enable the communication. According to thiscommunication system, since it is not necessary to additionally installnew hardware dedicated to communication, it is possible to minimize thesystem scale, cost, and so on.

When the present disclosure is used for host-vehicle position estimationand host-vehicle route prediction, one detecting device 2 may be used,or a plurality of detecting devices 2 may be used. For example,detecting devices 2 provided at the front, rear, left, and right sidesmay be used. Only the number of imaging devices 100 may be two or more,and the image processing and computation may be performed by one chip.

The detecting device 2 according to the present embodiment can bedesirably mounted on an aircraft, such as a drone, similarly to thedetecting device 1 according to the first embodiment.

(Others)

Although the imaging device 100 and the ISP 300 have been describedabove as being able to be mounted on the same chip, the imaging device100, the ISP 300, and the controller 500 can also be mounted on thechip. When such a chip is used, processing up to the computationalprocessing for the speed, the acceleration, and so on can be realized byone chip. In recent years, there have been demands for an increase indata processing speed, a reduction in power consumption, a reduction inchip size, and a reduction in cost. In such a perspective, theconfiguration implemented by one chip can be said to be optimum.

Although an operation example of an imaging device having a plurality ofunit pixels including a photoelectric conversion layer has been mainlydescribed hereinabove, for example, image capture can be performed usingan imaging device using known silicon PDs. In this case,multiple-exposure image data may be obtained by performing sensitivitymodulation through change of the exposure length between a plurality ofexposures.

Although an example in which a global shutter is realized by controllinga bias voltage to be applied to the photoelectric conversion layer hasbeen described above, the present disclosure is not limited thereto. Forexample, although the number of constituent elements increases,provision of electrical-charge transfer transistors andelectrical-charge storage capacitors provides advantages that aresimilar to those of controlling the bias voltage. Also, with regard tothe multiple exposures, provision of electrical-charge transfertransistors and electrical-charge storage capacitors also provideadvantages that are similar to those of controlling the bias voltage.

Hereinabove, the description has been given of an example in which thedetecting device 2 is mainly mounted on a moving body to detect thespeed of the moving body. However, when the detecting device 2 ismounted on a stationary body, and the stationary body images a movingbody, the absolute speed of the moving body can also be detected. Forexample, installing the detecting device 2 on a traffic light makes itpossible to crack down on speed violations of traveling vehicles.

A detection result of the traveling direction of a surrounding vehicle,the detection result being obtained by the vehicle-traveling controlsystem 1000, can be used for, for example, automatic traveling controlfor controlling accelerating and decelerating of the host vehicle.Alternatively, in a system that assists a driving operation, the driverof the host vehicle may accelerate or decelerate the host vehicle byoperating a brake and a gas pedal in accordance with the detectionresult. For example, the distance to a vehicle traveling ahead may bedetected based on the size of an image of the license plate of thevehicle traveling ahead, and when it is detected that the distance hasbecome smaller than a predetermined value, the brake of the host vehiclemay be actuated. Alternatively, a warning may be issued to the driver ofthe host vehicle so as to decelerate. Also, when it is detected that thedistance to the vehicle ahead becomes larger than a predetermined value,the gas pedal of the host vehicle may be actuated. Alternatively, awarning may be issued to the driver of the host vehicle so as toaccelerate.

The detecting device, the detecting method, and the vehicle-travelingcontrol system in the present disclosure are desirably utilized for anymoving body or stationary body that is required to have the ability todetect a relative traveling direction, a relative speed, an absolutetraveling direction, and an absolute speed.

What is claimed is:
 1. An imaging device comprising: a pixel including:a first electrode; a second electrode facing the first electrode; aphotoelectric conversion layer between the first electrode and thesecond electrode, the photoelectric conversion layer converting lightinto signal charge; and a charge accumulation region coupled to thesecond electrode, the charge accumulation region accumulating the signalcharge, wherein the pixel captures first data in a first exposure periodand captures second data in a second exposure period different from thefirst exposure period, the first exposure period and the second exposureperiod being included in a frame period, a length of the first exposureperiod is different from a length of the second exposure period, and theimaging device genetates multiple-exposure image data including at leastthe first data and the second data.
 2. The imaging device according toclaim 1, further comprising voltage control circuitry that supplies afirst voltage to the first electrode in the first exposure period andsupplies a second voltage to the first electrode in the second exposureperiod.
 3. The imaging device according to claim 2, wherein the firstvoltage is the same as the second voltage.
 4. The imaging deviceaccording to claim 2, wherein the voltage control circuitry supplies athird voltage to the first electrode in a non-exposure period providedbetween the first exposure period and the second exposure period, thethird voltage being different from the first voltage and the secondvoltage, and a potential difference between the first electrode and thesecond electrode in the non-exposure period is less than a potentialdifference between the first electrode and the second electrode in thefirst exposure period and the second exposure period.
 5. The imagingdevice according to claim 4, wherein the signal charge is notaccumulated in the charge accumulation region in the non-exposureperiod.
 6. A detection system comprising: the imaging device accordingto claim 1; and a processor that detects a motion state of an objectimaged by the imaging device, based on the first data and the seconddata included in the multiple-exposure image data.
 7. The detectionsystem according to claim 6, wherein the processor detects a speed ofthe object.
 8. The detection system according to claim 6, wherein theprocessor detects an acceleration of the object.
 9. A detection systemcomprising: the imaging device according to the claim 1; and a processorthat detects a moving object among objects imaged by the imaging device,based on the first data and the second data included in themultiple-exposure image data.
 10. A detection system comprising: theimaging device according to claim 1, installed on a moving body; and aprocessor that detects a relative motion state of the moving body withrespect to an object imaged by the imaging device, based on the firstdata and the second data included in the multiple-exposure image data.11. The detection system according to claim 10, wherein the processordetects a speed of the moving body with respect to the object.
 12. Thedetection system according to claim 10, wherein the processor detects anacceleration of the moving body with respect to the object.